https://github.com/hongtaoh/32vis
Tip revision: 9960413711b0efb1f51ff7cce3548d259be8d8cb authored by Hongtao Hao on 24 May 2025, 20:13:11 UTC
Update README.md
Update README.md
Tip revision: 9960413
Fields_of_study_Statistics_and_Visuals.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "47f4ad8f",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"from collections import Counter\n",
"import seaborn as sns\n",
"import matplotlib\n",
"font = {'family' : 'Arial',\n",
" 'weight' : 'normal',\n",
" 'size' : 16}\n",
"matplotlib.rc('font', **font)\n",
"import altair as alt\n",
"pd.set_option('display.max_rows', 500)\n",
"import numpy as np"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "233f87d5",
"metadata": {},
"outputs": [],
"source": [
"VISPUBDATA_PLUS = pd.read_csv('../data/processed/vispubdata_plus.csv')\n",
"OPENALEX_CONCEPT_DF = pd.read_csv('../data/processed/openalex_concept_df.csv')\n",
"REF_DF = pd.read_csv('../data/processed/large/openalex_reference_concept_df.csv')\n",
"CIT_DF = pd.read_csv('../data/processed/large/openalex_citation_concept_df.csv')\n",
"REF_ID_NAME = 'Reference OpenAlex ID'\n",
"CIT_ID_NAME = 'Citation Paper OpenAlex ID'\n",
"\n",
"REF_DF = REF_DF[REF_DF[REF_ID_NAME].notnull()]\n",
"CIT_DF = CIT_DF[CIT_DF[CIT_ID_NAME].notnull()]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "58d15a15",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Reference</th>\n",
" <th>Reference OpenAlex Year</th>\n",
" <th>Reference OpenAlex ID</th>\n",
" <th>Reference OpenAlex Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>https://openalex.org/W2888685797</td>\n",
" <td>2018</td>\n",
" <td>W2888685797</td>\n",
" <td>DeepTracker: Visualizing the Training Process ...</td>\n",
" <td>13</td>\n",
" <td>1</td>\n",
" <td>Computer science</td>\n",
" <td>https://openalex.org/C41008148</td>\n",
" <td>https://www.wikidata.org/wiki/Q21198</td>\n",
" <td>0</td>\n",
" <td>0.900810</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>https://openalex.org/W2888685797</td>\n",
" <td>2018</td>\n",
" <td>W2888685797</td>\n",
" <td>DeepTracker: Visualizing the Training Process ...</td>\n",
" <td>13</td>\n",
" <td>2</td>\n",
" <td>Convolutional neural network</td>\n",
" <td>https://openalex.org/C81363708</td>\n",
" <td>https://www.wikidata.org/wiki/Q17084460</td>\n",
" <td>2</td>\n",
" <td>0.765918</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>https://openalex.org/W2888685797</td>\n",
" <td>2018</td>\n",
" <td>W2888685797</td>\n",
" <td>DeepTracker: Visualizing the Training Process ...</td>\n",
" <td>13</td>\n",
" <td>3</td>\n",
" <td>Process (computing)</td>\n",
" <td>https://openalex.org/C98045186</td>\n",
" <td>https://www.wikidata.org/wiki/Q205663</td>\n",
" <td>2</td>\n",
" <td>0.669036</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>https://openalex.org/W2888685797</td>\n",
" <td>2018</td>\n",
" <td>W2888685797</td>\n",
" <td>DeepTracker: Visualizing the Training Process ...</td>\n",
" <td>13</td>\n",
" <td>4</td>\n",
" <td>Artificial intelligence</td>\n",
" <td>https://openalex.org/C154945302</td>\n",
" <td>https://www.wikidata.org/wiki/Q11660</td>\n",
" <td>1</td>\n",
" <td>0.602289</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>https://openalex.org/W2888685797</td>\n",
" <td>2018</td>\n",
" <td>W2888685797</td>\n",
" <td>DeepTracker: Visualizing the Training Process ...</td>\n",
" <td>13</td>\n",
" <td>5</td>\n",
" <td>Training (meteorology)</td>\n",
" <td>https://openalex.org/C2777211547</td>\n",
" <td>https://www.wikidata.org/wiki/Q17141490</td>\n",
" <td>2</td>\n",
" <td>0.533716</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Reference Reference OpenAlex Year \\\n",
"0 https://openalex.org/W2888685797 2018 \n",
"1 https://openalex.org/W2888685797 2018 \n",
"2 https://openalex.org/W2888685797 2018 \n",
"3 https://openalex.org/W2888685797 2018 \n",
"4 https://openalex.org/W2888685797 2018 \n",
"\n",
" Reference OpenAlex ID Reference OpenAlex Title \\\n",
"0 W2888685797 DeepTracker: Visualizing the Training Process ... \n",
"1 W2888685797 DeepTracker: Visualizing the Training Process ... \n",
"2 W2888685797 DeepTracker: Visualizing the Training Process ... \n",
"3 W2888685797 DeepTracker: Visualizing the Training Process ... \n",
"4 W2888685797 DeepTracker: Visualizing the Training Process ... \n",
"\n",
" Number of Concepts Index of Concept Concept \\\n",
"0 13 1 Computer science \n",
"1 13 2 Convolutional neural network \n",
"2 13 3 Process (computing) \n",
"3 13 4 Artificial intelligence \n",
"4 13 5 Training (meteorology) \n",
"\n",
" Concept ID Wikidata \\\n",
"0 https://openalex.org/C41008148 https://www.wikidata.org/wiki/Q21198 \n",
"1 https://openalex.org/C81363708 https://www.wikidata.org/wiki/Q17084460 \n",
"2 https://openalex.org/C98045186 https://www.wikidata.org/wiki/Q205663 \n",
"3 https://openalex.org/C154945302 https://www.wikidata.org/wiki/Q11660 \n",
"4 https://openalex.org/C2777211547 https://www.wikidata.org/wiki/Q17141490 \n",
"\n",
" Level Score \n",
"0 0 0.900810 \n",
"1 2 0.765918 \n",
"2 2 0.669036 \n",
"3 1 0.602289 \n",
"4 2 0.533716 "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ref_unique = pd.read_csv('../data/processed/openalex_reference_concept_df_unique.csv')\n",
"ref_unique.head()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "33213748",
"metadata": {},
"outputs": [
{
"data": {
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"<div>\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Citation Paper Year</th>\n",
" <th>Citation Paper OpenAlex ID</th>\n",
" <th>Citation Ppaer OpenAlex Title</th>\n",
" <th>Citation Paper OpenAlex DOI</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2022.0</td>\n",
" <td>W4281736408</td>\n",
" <td>DramatVis Personae: Visual Text Analytics for ...</td>\n",
" <td>https://doi.org/10.1145/3532106.3533526</td>\n",
" <td>8.0</td>\n",
" <td>1.0</td>\n",
" <td>Analytics</td>\n",
" <td>https://openalex.org/C79158427</td>\n",
" <td>https://www.wikidata.org/wiki/Q485396</td>\n",
" <td>2.0</td>\n",
" <td>0.704162</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2022.0</td>\n",
" <td>W4281736408</td>\n",
" <td>DramatVis Personae: Visual Text Analytics for ...</td>\n",
" <td>https://doi.org/10.1145/3532106.3533526</td>\n",
" <td>8.0</td>\n",
" <td>2.0</td>\n",
" <td>Computer science</td>\n",
" <td>https://openalex.org/C41008148</td>\n",
" <td>https://www.wikidata.org/wiki/Q21198</td>\n",
" <td>0.0</td>\n",
" <td>0.703784</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2022.0</td>\n",
" <td>W4281736408</td>\n",
" <td>DramatVis Personae: Visual Text Analytics for ...</td>\n",
" <td>https://doi.org/10.1145/3532106.3533526</td>\n",
" <td>8.0</td>\n",
" <td>3.0</td>\n",
" <td>Visual analytics</td>\n",
" <td>https://openalex.org/C59732488</td>\n",
" <td>https://www.wikidata.org/wiki/Q2528440</td>\n",
" <td>3.0</td>\n",
" <td>0.638154</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2022.0</td>\n",
" <td>W4281736408</td>\n",
" <td>DramatVis Personae: Visual Text Analytics for ...</td>\n",
" <td>https://doi.org/10.1145/3532106.3533526</td>\n",
" <td>8.0</td>\n",
" <td>4.0</td>\n",
" <td>Data science</td>\n",
" <td>https://openalex.org/C2522767166</td>\n",
" <td>https://www.wikidata.org/wiki/Q2374463</td>\n",
" <td>1.0</td>\n",
" <td>0.608217</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2022.0</td>\n",
" <td>W4281736408</td>\n",
" <td>DramatVis Personae: Visual Text Analytics for ...</td>\n",
" <td>https://doi.org/10.1145/3532106.3533526</td>\n",
" <td>8.0</td>\n",
" <td>5.0</td>\n",
" <td>Cultural analytics</td>\n",
" <td>https://openalex.org/C545860419</td>\n",
" <td>https://www.wikidata.org/wiki/Q5193251</td>\n",
" <td>5.0</td>\n",
" <td>0.428023</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1578279</th>\n",
" <td>2021.0</td>\n",
" <td>W3153872560</td>\n",
" <td>Randomized Algorithms for Scientific Computing...</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>3.0</td>\n",
" <td>Robustness (evolution)</td>\n",
" <td>https://openalex.org/C63479239</td>\n",
" <td>https://www.wikidata.org/wiki/Q7353546</td>\n",
" <td>3.0</td>\n",
" <td>0.458825</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1578280</th>\n",
" <td>2021.0</td>\n",
" <td>W3153872560</td>\n",
" <td>Randomized Algorithms for Scientific Computing...</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>4.0</td>\n",
" <td>Randomized algorithm</td>\n",
" <td>https://openalex.org/C128669082</td>\n",
" <td>https://www.wikidata.org/wiki/Q583461</td>\n",
" <td>2.0</td>\n",
" <td>0.424658</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1578281</th>\n",
" <td>2021.0</td>\n",
" <td>W3153872560</td>\n",
" <td>Randomized Algorithms for Scientific Computing...</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>5.0</td>\n",
" <td>Data science</td>\n",
" <td>https://openalex.org/C2522767166</td>\n",
" <td>https://www.wikidata.org/wiki/Q2374463</td>\n",
" <td>1.0</td>\n",
" <td>0.403737</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1578282</th>\n",
" <td>2021.0</td>\n",
" <td>W3153872560</td>\n",
" <td>Randomized Algorithms for Scientific Computing...</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>6.0</td>\n",
" <td>Artificial intelligence</td>\n",
" <td>https://openalex.org/C154945302</td>\n",
" <td>https://www.wikidata.org/wiki/Q11660</td>\n",
" <td>1.0</td>\n",
" <td>0.385798</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1578283</th>\n",
" <td>2021.0</td>\n",
" <td>W3153872560</td>\n",
" <td>Randomized Algorithms for Scientific Computing...</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>7.0</td>\n",
" <td>Algorithm</td>\n",
" <td>https://openalex.org/C11413529</td>\n",
" <td>https://www.wikidata.org/wiki/Q8366</td>\n",
" <td>1.0</td>\n",
" <td>0.336754</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>603800 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" Citation Paper Year Citation Paper OpenAlex ID \\\n",
"0 2022.0 W4281736408 \n",
"1 2022.0 W4281736408 \n",
"2 2022.0 W4281736408 \n",
"3 2022.0 W4281736408 \n",
"4 2022.0 W4281736408 \n",
"... ... ... \n",
"1578279 2021.0 W3153872560 \n",
"1578280 2021.0 W3153872560 \n",
"1578281 2021.0 W3153872560 \n",
"1578282 2021.0 W3153872560 \n",
"1578283 2021.0 W3153872560 \n",
"\n",
" Citation Ppaer OpenAlex Title \\\n",
"0 DramatVis Personae: Visual Text Analytics for ... \n",
"1 DramatVis Personae: Visual Text Analytics for ... \n",
"2 DramatVis Personae: Visual Text Analytics for ... \n",
"3 DramatVis Personae: Visual Text Analytics for ... \n",
"4 DramatVis Personae: Visual Text Analytics for ... \n",
"... ... \n",
"1578279 Randomized Algorithms for Scientific Computing... \n",
"1578280 Randomized Algorithms for Scientific Computing... \n",
"1578281 Randomized Algorithms for Scientific Computing... \n",
"1578282 Randomized Algorithms for Scientific Computing... \n",
"1578283 Randomized Algorithms for Scientific Computing... \n",
"\n",
" Citation Paper OpenAlex DOI Number of Concepts \\\n",
"0 https://doi.org/10.1145/3532106.3533526 8.0 \n",
"1 https://doi.org/10.1145/3532106.3533526 8.0 \n",
"2 https://doi.org/10.1145/3532106.3533526 8.0 \n",
"3 https://doi.org/10.1145/3532106.3533526 8.0 \n",
"4 https://doi.org/10.1145/3532106.3533526 8.0 \n",
"... ... ... \n",
"1578279 NaN 7.0 \n",
"1578280 NaN 7.0 \n",
"1578281 NaN 7.0 \n",
"1578282 NaN 7.0 \n",
"1578283 NaN 7.0 \n",
"\n",
" Index of Concept Concept \\\n",
"0 1.0 Analytics \n",
"1 2.0 Computer science \n",
"2 3.0 Visual analytics \n",
"3 4.0 Data science \n",
"4 5.0 Cultural analytics \n",
"... ... ... \n",
"1578279 3.0 Robustness (evolution) \n",
"1578280 4.0 Randomized algorithm \n",
"1578281 5.0 Data science \n",
"1578282 6.0 Artificial intelligence \n",
"1578283 7.0 Algorithm \n",
"\n",
" Concept ID \\\n",
"0 https://openalex.org/C79158427 \n",
"1 https://openalex.org/C41008148 \n",
"2 https://openalex.org/C59732488 \n",
"3 https://openalex.org/C2522767166 \n",
"4 https://openalex.org/C545860419 \n",
"... ... \n",
"1578279 https://openalex.org/C63479239 \n",
"1578280 https://openalex.org/C128669082 \n",
"1578281 https://openalex.org/C2522767166 \n",
"1578282 https://openalex.org/C154945302 \n",
"1578283 https://openalex.org/C11413529 \n",
"\n",
" Wikidata Level Score \n",
"0 https://www.wikidata.org/wiki/Q485396 2.0 0.704162 \n",
"1 https://www.wikidata.org/wiki/Q21198 0.0 0.703784 \n",
"2 https://www.wikidata.org/wiki/Q2528440 3.0 0.638154 \n",
"3 https://www.wikidata.org/wiki/Q2374463 1.0 0.608217 \n",
"4 https://www.wikidata.org/wiki/Q5193251 5.0 0.428023 \n",
"... ... ... ... \n",
"1578279 https://www.wikidata.org/wiki/Q7353546 3.0 0.458825 \n",
"1578280 https://www.wikidata.org/wiki/Q583461 2.0 0.424658 \n",
"1578281 https://www.wikidata.org/wiki/Q2374463 1.0 0.403737 \n",
"1578282 https://www.wikidata.org/wiki/Q11660 1.0 0.385798 \n",
"1578283 https://www.wikidata.org/wiki/Q8366 1.0 0.336754 \n",
"\n",
"[603800 rows x 11 columns]"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cit_unique = CIT_DF.iloc[:, 4:].drop_duplicates()\n",
"cit_unique"
]
},
{
"cell_type": "markdown",
"id": "3a77bd96",
"metadata": {},
"source": [
"### How many VIS, REF, and CIT papers have L0 Concept"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "ab0f7d70",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3240"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis = OPENALEX_CONCEPT_DF.copy()\n",
"# total paper number:\n",
"len(list(set(vis.DOI)))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "62fb279d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3238"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# number of VIS papers that have at least one L0 concept\n",
"vis_l0_dois = vis[vis.Level == 0].DOI.tolist()\n",
"len(list(set(vis_l0_dois)))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "8e76e268",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9993827160493827"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(list(set(vis_l0_dois))) / len(list(set(vis.DOI)))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "38ffd0a0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"270"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# how many VIS papers have multiple L0 Concepts\n",
"vis_multiple_l0 = list(set(\n",
" [x for x in vis_l0_dois if vis_l0_dois.count(x) > 1]))\n",
"len(vis_multiple_l0)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "a16307c0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.08333333333333333"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(vis_multiple_l0) / len(list(set(vis.DOI)))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "e24bea17",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"39817"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Total number of unique ref papers\n",
"ref_ids = ref_unique['Reference OpenAlex ID'].tolist()\n",
"len(list(set(ref_ids)))"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "9773490b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"39650"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# how many ref papers have at least one L0 concept\n",
"ref_l0_ids = ref_unique[ref_unique.Level == 0]['Reference OpenAlex ID'].tolist()\n",
"len(list(set(ref_l0_ids)))"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "08b2de96",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9958058115880152"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(list(set(ref_l0_ids))) / len(list(set(ref_ids)))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "610f5860",
"metadata": {},
"outputs": [],
"source": [
"dic = dict(Counter(ref_l0_ids))\n",
"# dff = pd.DataFrame(dic.items(), columns = ['id', 'count'])\n",
"ref_multiple = []\n",
"for key,value in dic.items():\n",
" if value > 1:\n",
" ref_multiple.append(key)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "f9d494a0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"7795"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# How many Ref papers have more than one L0 Concept\n",
"len(ref_multiple)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "bc079949",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.19577065072707636"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(ref_multiple) / len(list(set(ref_ids)))"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "14104052",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"60272"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Total number of unique cit papers\n",
"cit_ids = cit_unique['Citation Paper OpenAlex ID'].tolist()\n",
"len(list(set(cit_ids)))"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "aa718b97",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"60128"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# how many cit papers have at least one L0 concept\n",
"cit_l0_ids = cit_unique[cit_unique.Level == 0]['Citation Paper OpenAlex ID'].tolist()\n",
"len(list(set(cit_l0_ids)))"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "ab41d845",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9976108308999203"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(list(set(cit_l0_ids))) / len(list(set(cit_ids)))"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "62254bed",
"metadata": {},
"outputs": [],
"source": [
"dic = dict(Counter(cit_l0_ids))\n",
"cit_multiple = []\n",
"for key,value in dic.items():\n",
" if value > 1:\n",
" cit_multiple.append(key)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "c1390948",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9201"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# How many cit papers have more than one L0 Concept\n",
"len(cit_multiple)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "ef2ce6a1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.1526579506238386"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(cit_multiple) / len(list(set(cit_ids)))"
]
},
{
"cell_type": "markdown",
"id": "d2d93a08",
"metadata": {},
"source": [
"#### Automation"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "9c5c4dfa",
"metadata": {},
"outputs": [],
"source": [
"vis_key = 'DOI'\n",
"ref_key = 'Reference OpenAlex ID'\n",
"cit_key = 'Citation Paper OpenAlex ID'"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "0f7825e4",
"metadata": {},
"outputs": [],
"source": [
"keys = [vis_key, ref_key, cit_key]"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "b5891316",
"metadata": {},
"outputs": [],
"source": [
"df_name_lists = ['vis', 'ref', 'cit']"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "0847b8a7",
"metadata": {},
"outputs": [],
"source": [
"vis_df = vis\n",
"ref_df = ref_unique\n",
"cit_df = cit_unique"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "ef315472",
"metadata": {},
"outputs": [],
"source": [
"dfs = [vis_df, ref_df, cit_df]"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "bc1329af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"There are a total of 3240 unique papers in vis\n",
"In vis, there are 17 unique L0 concepts\n",
"In vis, 3238 (99.9%) papers have at least one L0 Concept; 270 (8.3%) have more than one\n",
"In vis, there are 122 unique L1 concepts\n",
"In vis, 3151 (97.3%) papers have at least one L1 Concept; 2643 (81.6%) have more than one\n",
"In vis, there are 2036 unique L2 concepts\n",
"In vis, 3224 (99.5%) papers have at least one L2 Concept; 3173 (97.89999999999999%) have more than one\n",
"In vis, there are 730 unique L3 concepts\n",
"In vis, 2717 (83.89999999999999%) papers have at least one L3 Concept; 1774 (54.800000000000004%) have more than one\n",
"------------------------------------------------\n",
"There are a total of 39817 unique papers in ref\n",
"In ref, there are 19 unique L0 concepts\n",
"In ref, 39650 (99.6%) papers have at least one L0 Concept; 7795 (19.6%) have more than one\n",
"In ref, there are 274 unique L1 concepts\n",
"In ref, 38038 (95.5%) papers have at least one L1 Concept; 30457 (76.5%) have more than one\n",
"In ref, there are 7905 unique L2 concepts\n",
"In ref, 38354 (96.3%) papers have at least one L2 Concept; 35920 (90.2%) have more than one\n",
"In ref, there are 5281 unique L3 concepts\n",
"In ref, 27057 (68.0%) papers have at least one L3 Concept; 14777 (37.1%) have more than one\n",
"------------------------------------------------\n",
"There are a total of 60272 unique papers in cit\n",
"In cit, there are 19 unique L0 concepts\n",
"In cit, 60128 (99.8%) papers have at least one L0 Concept; 9201 (15.299999999999999%) have more than one\n",
"In cit, there are 274 unique L1 concepts\n",
"In cit, 58159 (96.5%) papers have at least one L1 Concept; 46966 (77.9%) have more than one\n",
"In cit, there are 8140 unique L2 concepts\n",
"In cit, 58400 (96.89999999999999%) papers have at least one L2 Concept; 55390 (91.9%) have more than one\n",
"In cit, there are 5333 unique L3 concepts\n",
"In cit, 41618 (69.1%) papers have at least one L3 Concept; 23036 (38.2%) have more than one\n",
"------------------------------------------------\n"
]
}
],
"source": [
"for idx, df in enumerate(dfs):\n",
" key = keys[idx]\n",
" df_name = df_name_lists[idx]\n",
" unique_ids = list(set(df[key]))\n",
" total = len(unique_ids)\n",
" print(f'There are a total of {total} unique papers in {df_name}')\n",
" for LEVEL in range(0, 4):\n",
"# if df_name == 'vis':\n",
" Level_concepts = df[df.Level == LEVEL].Concept\n",
" unique_Level_concepts = list(set(Level_concepts))\n",
" print(f'In {df_name}, there are {len(unique_Level_concepts)} unique L{LEVEL} concepts')\n",
" level_ids = df[df.Level == LEVEL][key].tolist()\n",
" unique_level_ids = list(set(level_ids))\n",
" sub_total = len(unique_level_ids)\n",
" ratio = round(sub_total / total, 3) * 100\n",
" dic = dict(Counter(level_ids))\n",
" id_multiple = []\n",
" for id,value in dic.items():\n",
" if value > 1:\n",
" id_multiple.append(id)\n",
" ratio_multiple = round(len(id_multiple) / total, 3) * 100\n",
" print(f'In {df_name}, {sub_total} ({ratio}%) papers have at least one L{LEVEL} Concept; {len(id_multiple)} ({(ratio_multiple)}%) have more than one')\n",
" print('------------------------------------------------')"
]
},
{
"cell_type": "markdown",
"id": "e0224ced",
"metadata": {},
"source": [
"### Visualize"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "5bda0b40",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3240"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_l0 = vis[vis.Level == 0]\n",
"vis_l0_concepts = vis_l0.Concept\n",
"len(list(set(vis.DOI)))"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "e2d272b2",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>concept</th>\n",
" <th>count</th>\n",
" <th>ratio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Computer science</td>\n",
" <td>3189</td>\n",
" <td>0.984</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Mathematics</td>\n",
" <td>185</td>\n",
" <td>0.057</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Physics</td>\n",
" <td>41</td>\n",
" <td>0.013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Geology</td>\n",
" <td>30</td>\n",
" <td>0.009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Materials science</td>\n",
" <td>16</td>\n",
" <td>0.005</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Medicine</td>\n",
" <td>9</td>\n",
" <td>0.003</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Psychology</td>\n",
" <td>9</td>\n",
" <td>0.003</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Environmental science</td>\n",
" <td>11</td>\n",
" <td>0.003</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Chemistry</td>\n",
" <td>7</td>\n",
" <td>0.002</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Biology</td>\n",
" <td>4</td>\n",
" <td>0.001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Geography</td>\n",
" <td>3</td>\n",
" <td>0.001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Business</td>\n",
" <td>3</td>\n",
" <td>0.001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Art</td>\n",
" <td>1</td>\n",
" <td>0.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Sociology</td>\n",
" <td>1</td>\n",
" <td>0.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Engineering</td>\n",
" <td>1</td>\n",
" <td>0.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Political science</td>\n",
" <td>1</td>\n",
" <td>0.000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Economics</td>\n",
" <td>1</td>\n",
" <td>0.000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" concept count ratio\n",
"0 Computer science 3189 0.984\n",
"1 Mathematics 185 0.057\n",
"3 Physics 41 0.013\n",
"2 Geology 30 0.009\n",
"11 Materials science 16 0.005\n",
"4 Medicine 9 0.003\n",
"7 Psychology 9 0.003\n",
"10 Environmental science 11 0.003\n",
"6 Chemistry 7 0.002\n",
"5 Biology 4 0.001\n",
"9 Geography 3 0.001\n",
"13 Business 3 0.001\n",
"14 Art 1 0.000\n",
"15 Sociology 1 0.000\n",
"8 Engineering 1 0.000\n",
"12 Political science 1 0.000\n",
"16 Economics 1 0.000"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_l0_dic = dict(Counter(vis_l0_concepts))\n",
"vis_l0_dic_df = pd.DataFrame(vis_l0_dic.items(), columns = ['concept', 'count'])\n",
"vis_l0_dic_df['ratio'] = round(\n",
" vis_l0_dic_df['count'] / len(list(set(vis.DOI))), 3)\n",
"vis_l0_dic_df.sort_values(by = 'ratio', ascending= False)"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "3f869b0d",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a4_dims = (8,6)\n",
"fig, ax = plt.subplots(figsize=a4_dims)\n",
"sns.countplot(x = vis_l0_concepts, order = vis_l0_concepts.value_counts().index)\n",
"plt.xticks(rotation=88)\n",
"plt.ylabel('Count (log)')\n",
"plt.yscale('log')\n",
"plt.savefig('../results/supp/vis_L0.pdf', bbox_inches = 'tight')"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "3872d00b",
"metadata": {},
"outputs": [],
"source": [
"ref_l0 = ref_unique[ref_unique.Level == 0]\n",
"ref_l0_concepts = ref_l0.Concept"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "ff356143",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>concept</th>\n",
" <th>count</th>\n",
" <th>ratio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Computer science</td>\n",
" <td>32513</td>\n",
" <td>0.817</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Mathematics</td>\n",
" <td>5466</td>\n",
" <td>0.137</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Psychology</td>\n",
" <td>2575</td>\n",
" <td>0.065</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Physics</td>\n",
" <td>1317</td>\n",
" <td>0.033</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Medicine</td>\n",
" <td>1056</td>\n",
" <td>0.027</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Biology</td>\n",
" <td>785</td>\n",
" <td>0.020</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Geography</td>\n",
" <td>630</td>\n",
" <td>0.016</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Geology</td>\n",
" <td>537</td>\n",
" <td>0.013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Sociology</td>\n",
" <td>473</td>\n",
" <td>0.012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>Environmental science</td>\n",
" <td>488</td>\n",
" <td>0.012</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Materials science</td>\n",
" <td>403</td>\n",
" <td>0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Business</td>\n",
" <td>330</td>\n",
" <td>0.008</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Chemistry</td>\n",
" <td>318</td>\n",
" <td>0.008</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Engineering</td>\n",
" <td>258</td>\n",
" <td>0.006</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Economics</td>\n",
" <td>192</td>\n",
" <td>0.005</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Political science</td>\n",
" <td>208</td>\n",
" <td>0.005</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Art</td>\n",
" <td>154</td>\n",
" <td>0.004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>History</td>\n",
" <td>134</td>\n",
" <td>0.003</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Philosophy</td>\n",
" <td>87</td>\n",
" <td>0.002</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" concept count ratio\n",
"0 Computer science 32513 0.817\n",
"1 Mathematics 5466 0.137\n",
"9 Psychology 2575 0.065\n",
"7 Physics 1317 0.033\n",
"2 Medicine 1056 0.027\n",
"5 Biology 785 0.020\n",
"6 Geography 630 0.016\n",
"13 Geology 537 0.013\n",
"11 Sociology 473 0.012\n",
"16 Environmental science 488 0.012\n",
"14 Materials science 403 0.010\n",
"12 Business 330 0.008\n",
"15 Chemistry 318 0.008\n",
"4 Engineering 258 0.006\n",
"3 Economics 192 0.005\n",
"10 Political science 208 0.005\n",
"17 Art 154 0.004\n",
"18 History 134 0.003\n",
"8 Philosophy 87 0.002"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ref_l0_dic = dict(Counter(ref_l0_concepts))\n",
"ref_l0_dic_df = pd.DataFrame(ref_l0_dic.items(), columns = ['concept', 'count'])\n",
"ref_l0_dic_df['ratio'] = round(\n",
" ref_l0_dic_df['count'] / len(list(set(ref_unique[ref_key]))),\n",
" 3)\n",
"ref_l0_dic_df.sort_values(by = 'ratio', ascending= False)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "5b58ae55",
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 576x432 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a4_dims = (8,6)\n",
"fig, ax = plt.subplots(figsize=a4_dims)\n",
"sns.countplot(x = ref_l0_concepts, order = ref_l0_concepts.value_counts().index)\n",
"plt.xticks(rotation=88)\n",
"plt.yscale('log')\n",
"plt.ylabel('Count (log)')\n",
"plt.savefig('../results/supp/ref_L0.pdf', bbox_inches = 'tight')"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "a159fc42",
"metadata": {},
"outputs": [],
"source": [
"cit_l0 = cit_unique[cit_unique.Level == 0]\n",
"cit_l0_concepts = cit_l0.Concept"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "22ea67a4",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>concept</th>\n",
" <th>count</th>\n",
" <th>ratio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Computer science</td>\n",
" <td>55008</td>\n",
" <td>0.913</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>Mathematics</td>\n",
" <td>4673</td>\n",
" <td>0.078</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Biology</td>\n",
" <td>1384</td>\n",
" <td>0.023</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Medicine</td>\n",
" <td>1252</td>\n",
" <td>0.021</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>Geography</td>\n",
" <td>1249</td>\n",
" <td>0.021</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>Psychology</td>\n",
" <td>1251</td>\n",
" <td>0.021</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>Physics</td>\n",
" <td>782</td>\n",
" <td>0.013</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Business</td>\n",
" <td>603</td>\n",
" <td>0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>Geology</td>\n",
" <td>611</td>\n",
" <td>0.010</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Materials science</td>\n",
" <td>519</td>\n",
" <td>0.009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Engineering</td>\n",
" <td>550</td>\n",
" <td>0.009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>Environmental science</td>\n",
" <td>467</td>\n",
" <td>0.008</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Political science</td>\n",
" <td>395</td>\n",
" <td>0.007</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Sociology</td>\n",
" <td>410</td>\n",
" <td>0.007</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>Chemistry</td>\n",
" <td>300</td>\n",
" <td>0.005</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>Art</td>\n",
" <td>247</td>\n",
" <td>0.004</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Philosophy</td>\n",
" <td>109</td>\n",
" <td>0.002</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>Economics</td>\n",
" <td>56</td>\n",
" <td>0.001</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>History</td>\n",
" <td>76</td>\n",
" <td>0.001</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" concept count ratio\n",
"0 Computer science 55008 0.913\n",
"17 Mathematics 4673 0.078\n",
"1 Biology 1384 0.023\n",
"4 Medicine 1252 0.021\n",
"7 Geography 1249 0.021\n",
"10 Psychology 1251 0.021\n",
"6 Physics 782 0.013\n",
"3 Business 603 0.010\n",
"11 Geology 611 0.010\n",
"15 Materials science 519 0.009\n",
"5 Engineering 550 0.009\n",
"8 Environmental science 467 0.008\n",
"9 Political science 395 0.007\n",
"2 Sociology 410 0.007\n",
"12 Chemistry 300 0.005\n",
"13 Art 247 0.004\n",
"18 Philosophy 109 0.002\n",
"14 Economics 56 0.001\n",
"16 History 76 0.001"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cit_l0_dic = dict(Counter(cit_l0_concepts))\n",
"cit_l0_dic_df = pd.DataFrame(cit_l0_dic.items(), columns = ['concept', 'count'])\n",
"cit_l0_dic_df['ratio'] = round(\n",
" cit_l0_dic_df['count'] / len(list(set(cit_unique[cit_key]))),\n",
" 3)\n",
"cit_l0_dic_df.sort_values(by = 'ratio', ascending= False)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "eefc70dd",
"metadata": {},
"outputs": [],
"source": [
"# cit_l0_dic = dict(Counter(cit_l0_concepts))\n",
"# cit_l0_dic_df = pd.DataFrame(cit_l0_dic.items(), columns = ['concept', 'count'])\n",
"# cit_l0_dic_df['ratio'] = round(\n",
"# cit_l0_dic_df['count'] / len(list(set(cit_unique[cit_key])),\n",
"# 3)\n",
"# cit_l0_dic_df.sort_values(by = 'ratio', ascending= False)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "d199d0d6",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"a4_dims = (8, 6)\n",
"fig, ax = plt.subplots(figsize=a4_dims)\n",
"sns.countplot(x = cit_l0_concepts, order = cit_l0_concepts.value_counts().index)\n",
"plt.xticks(rotation=88)\n",
"plt.ylabel('Count (log)')\n",
"plt.yscale('log')\n",
"plt.savefig('../results/supp/cit_L0.pdf', bbox_inches = 'tight')"
]
},
{
"cell_type": "markdown",
"id": "7bc0ad42",
"metadata": {},
"source": [
"## Popularity trends\n",
"\n",
"I want to see which concepts do not belong to cs."
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "9e4c2b89",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>107</th>\n",
" <td>2001</td>\n",
" <td>10.1109/VISUAL.2001.964489</td>\n",
" <td>Point set surfaces</td>\n",
" <td>3</td>\n",
" <td>2</td>\n",
" <td>Set (abstract data type)</td>\n",
" <td>https://openalex.org/C177264268</td>\n",
" <td>https://www.wikidata.org/wiki/Q1514741</td>\n",
" <td>2</td>\n",
" <td>0.533244</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI Title Number of Concepts \\\n",
"107 2001 10.1109/VISUAL.2001.964489 Point set surfaces 3 \n",
"\n",
" Index of Concept Concept \\\n",
"107 2 Set (abstract data type) \n",
"\n",
" Concept ID Wikidata \\\n",
"107 https://openalex.org/C177264268 https://www.wikidata.org/wiki/Q1514741 \n",
"\n",
" Level Score \n",
"107 2 0.533244 "
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L2 = vis[vis.Level == 2]\n",
"vis_L2[vis_L2.Concept == 'Set (abstract data type)'].head(1)\n",
"# it is cs"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "8e34e26c",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>294</th>\n",
" <td>2014</td>\n",
" <td>10.1109/TVCG.2014.2346248</td>\n",
" <td>UpSet: Visualization of Intersecting Sets</td>\n",
" <td>14</td>\n",
" <td>3</td>\n",
" <td>Context (archaeology)</td>\n",
" <td>https://openalex.org/C2779343474</td>\n",
" <td>https://www.wikidata.org/wiki/Q3109175</td>\n",
" <td>2</td>\n",
" <td>0.638373</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"294 2014 10.1109/TVCG.2014.2346248 \n",
"\n",
" Title Number of Concepts \\\n",
"294 UpSet: Visualization of Intersecting Sets 14 \n",
"\n",
" Index of Concept Concept \\\n",
"294 3 Context (archaeology) \n",
"\n",
" Concept ID Wikidata \\\n",
"294 https://openalex.org/C2779343474 https://www.wikidata.org/wiki/Q3109175 \n",
"\n",
" Level Score \n",
"294 2 0.638373 "
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L2[vis_L2.Concept == 'Context (archaeology)'].head(1)\n",
"# not computer science"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "5a41af43",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>708</th>\n",
" <td>2011</td>\n",
" <td>10.1109/VAST.2011.6102456</td>\n",
" <td>SensePlace2: GeoTwitter analytics support for ...</td>\n",
" <td>10</td>\n",
" <td>4</td>\n",
" <td>Analytics</td>\n",
" <td>https://openalex.org/C79158427</td>\n",
" <td>https://www.wikidata.org/wiki/Q485396</td>\n",
" <td>2</td>\n",
" <td>0.526905</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"708 2011 10.1109/VAST.2011.6102456 \n",
"\n",
" Title Number of Concepts \\\n",
"708 SensePlace2: GeoTwitter analytics support for ... 10 \n",
"\n",
" Index of Concept Concept Concept ID \\\n",
"708 4 Analytics https://openalex.org/C79158427 \n",
"\n",
" Wikidata Level Score \n",
"708 https://www.wikidata.org/wiki/Q485396 2 0.526905 "
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L2[vis_L2.Concept == 'Analytics'].head(1)\n",
"# cs"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "34fc65e5",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" }\n",
"\n",
" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>608</th>\n",
" <td>1997</td>\n",
" <td>10.1109/VISUAL.1997.663875</td>\n",
" <td>The contour spectrum</td>\n",
" <td>12</td>\n",
" <td>10</td>\n",
" <td>Pattern recognition (psychology)</td>\n",
" <td>https://openalex.org/C153180895</td>\n",
" <td>https://www.wikidata.org/wiki/Q7148389</td>\n",
" <td>2</td>\n",
" <td>0.333173</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI Title \\\n",
"608 1997 10.1109/VISUAL.1997.663875 The contour spectrum \n",
"\n",
" Number of Concepts Index of Concept Concept \\\n",
"608 12 10 Pattern recognition (psychology) \n",
"\n",
" Concept ID Wikidata \\\n",
"608 https://openalex.org/C153180895 https://www.wikidata.org/wiki/Q7148389 \n",
"\n",
" Level Score \n",
"608 2 0.333173 "
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L2[vis_L2.Concept == 'Pattern recognition (psychology)'].head(1)\n",
"# cs"
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "1bce340b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>204</th>\n",
" <td>2009</td>\n",
" <td>10.1109/TVCG.2009.111</td>\n",
" <td>A Nested Model for Visualization Design and Va...</td>\n",
" <td>16</td>\n",
" <td>3</td>\n",
" <td>Domain (mathematical analysis)</td>\n",
" <td>https://openalex.org/C36503486</td>\n",
" <td>https://www.wikidata.org/wiki/Q11235244</td>\n",
" <td>2</td>\n",
" <td>0.555469</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"204 2009 10.1109/TVCG.2009.111 \n",
"\n",
" Title Number of Concepts \\\n",
"204 A Nested Model for Visualization Design and Va... 16 \n",
"\n",
" Index of Concept Concept \\\n",
"204 3 Domain (mathematical analysis) \n",
"\n",
" Concept ID Wikidata \\\n",
"204 https://openalex.org/C36503486 https://www.wikidata.org/wiki/Q11235244 \n",
"\n",
" Level Score \n",
"204 2 0.555469 "
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L2[vis_L2.Concept == 'Domain (mathematical analysis)'].head(1)\n",
"# math"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "27ba6bfe",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>49</th>\n",
" <td>2006</td>\n",
" <td>10.1109/TVCG.2006.147</td>\n",
" <td>Hierarchical Edge Bundles: Visualization of Ad...</td>\n",
" <td>11</td>\n",
" <td>6</td>\n",
" <td>Graph</td>\n",
" <td>https://openalex.org/C132525143</td>\n",
" <td>https://www.wikidata.org/wiki/Q141488</td>\n",
" <td>2</td>\n",
" <td>0.502342</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"49 2006 10.1109/TVCG.2006.147 \n",
"\n",
" Title Number of Concepts \\\n",
"49 Hierarchical Edge Bundles: Visualization of Ad... 11 \n",
"\n",
" Index of Concept Concept Concept ID \\\n",
"49 6 Graph https://openalex.org/C132525143 \n",
"\n",
" Wikidata Level Score \n",
"49 https://www.wikidata.org/wiki/Q141488 2 0.502342 "
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L2[vis_L2.Concept == 'Graph'].head(1)\n",
"# cs"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "169d6143",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
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" }\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>139</th>\n",
" <td>2007</td>\n",
" <td>10.1109/TVCG.2007.70515</td>\n",
" <td>Toward a Deeper Understanding of the Role of I...</td>\n",
" <td>9</td>\n",
" <td>4</td>\n",
" <td>Focus (optics)</td>\n",
" <td>https://openalex.org/C192209626</td>\n",
" <td>https://www.wikidata.org/wiki/Q190909</td>\n",
" <td>2</td>\n",
" <td>0.560184</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"139 2007 10.1109/TVCG.2007.70515 \n",
"\n",
" Title Number of Concepts \\\n",
"139 Toward a Deeper Understanding of the Role of I... 9 \n",
"\n",
" Index of Concept Concept Concept ID \\\n",
"139 4 Focus (optics) https://openalex.org/C192209626 \n",
"\n",
" Wikidata Level Score \n",
"139 https://www.wikidata.org/wiki/Q190909 2 0.560184 "
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L2[vis_L2.Concept == 'Focus (optics)'].head(1)\n",
"# physics"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "61c18f44",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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" vertical-align: top;\n",
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"\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
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" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2011</td>\n",
" <td>10.1109/TVCG.2011.185</td>\n",
" <td>D³ Data-Driven Documents</td>\n",
" <td>15</td>\n",
" <td>4</td>\n",
" <td>Representation (politics)</td>\n",
" <td>https://openalex.org/C2776359362</td>\n",
" <td>https://www.wikidata.org/wiki/Q2145286</td>\n",
" <td>3</td>\n",
" <td>0.619485</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI Title Number of Concepts \\\n",
"3 2011 10.1109/TVCG.2011.185 D³ Data-Driven Documents 15 \n",
"\n",
" Index of Concept Concept \\\n",
"3 4 Representation (politics) \n",
"\n",
" Concept ID Wikidata \\\n",
"3 https://openalex.org/C2776359362 https://www.wikidata.org/wiki/Q2145286 \n",
"\n",
" Level Score \n",
"3 3 0.619485 "
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L3 = vis[vis.Level == 3]\n",
"vis_L3[vis_L3.Concept == 'Representation (politics)'].head(1)\n",
"# political science"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "67547e8e",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" <th>DOI</th>\n",
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" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
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" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>1991</td>\n",
" <td>10.1109/VISUAL.1991.175782</td>\n",
" <td>The asymptotic decider: resolving the ambiguit...</td>\n",
" <td>11</td>\n",
" <td>5</td>\n",
" <td>Isosurface</td>\n",
" <td>https://openalex.org/C45107383</td>\n",
" <td>https://www.wikidata.org/wiki/Q1311829</td>\n",
" <td>3</td>\n",
" <td>0.488049</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"173 1991 10.1109/VISUAL.1991.175782 \n",
"\n",
" Title Number of Concepts \\\n",
"173 The asymptotic decider: resolving the ambiguit... 11 \n",
"\n",
" Index of Concept Concept Concept ID \\\n",
"173 5 Isosurface https://openalex.org/C45107383 \n",
"\n",
" Wikidata Level Score \n",
"173 https://www.wikidata.org/wiki/Q1311829 3 0.488049 "
]
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L3[vis_L3.Concept == 'Isosurface'].head(1)\n",
"# cs"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "b29ae339",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>254</th>\n",
" <td>2007</td>\n",
" <td>10.1109/TVCG.2007.70582</td>\n",
" <td>NodeTrix: a Hybrid Visualization of Social Net...</td>\n",
" <td>15</td>\n",
" <td>14</td>\n",
" <td>Graph drawing</td>\n",
" <td>https://openalex.org/C112953755</td>\n",
" <td>https://www.wikidata.org/wiki/Q739462</td>\n",
" <td>3</td>\n",
" <td>0.430049</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"254 2007 10.1109/TVCG.2007.70582 \n",
"\n",
" Title Number of Concepts \\\n",
"254 NodeTrix: a Hybrid Visualization of Social Net... 15 \n",
"\n",
" Index of Concept Concept Concept ID \\\n",
"254 14 Graph drawing https://openalex.org/C112953755 \n",
"\n",
" Wikidata Level Score \n",
"254 https://www.wikidata.org/wiki/Q739462 3 0.430049 "
]
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L3[vis_L3.Concept == 'Graph drawing'].head(1)\n",
"# cs"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "1b4ec4b4",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
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" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>2007</td>\n",
" <td>10.1109/TVCG.2007.70551</td>\n",
" <td>Efficient Computation and Visualization of Coh...</td>\n",
" <td>10</td>\n",
" <td>7</td>\n",
" <td>Flow visualization</td>\n",
" <td>https://openalex.org/C83893533</td>\n",
" <td>https://www.wikidata.org/wiki/Q5462121</td>\n",
" <td>3</td>\n",
" <td>0.503467</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"2014 2007 10.1109/TVCG.2007.70551 \n",
"\n",
" Title Number of Concepts \\\n",
"2014 Efficient Computation and Visualization of Coh... 10 \n",
"\n",
" Index of Concept Concept Concept ID \\\n",
"2014 7 Flow visualization https://openalex.org/C83893533 \n",
"\n",
" Wikidata Level Score \n",
"2014 https://www.wikidata.org/wiki/Q5462121 3 0.503467 "
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L3[vis_L3.Concept == 'Flow visualization'].head(1)\n",
"# not cs"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "93b7ebe7",
"metadata": {},
"outputs": [
{
"data": {
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" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>69</th>\n",
" <td>2003</td>\n",
" <td>10.1109/VISUAL.2003.1250384</td>\n",
" <td>Acceleration techniques for GPU-based volume r...</td>\n",
" <td>16</td>\n",
" <td>3</td>\n",
" <td>Volume rendering</td>\n",
" <td>https://openalex.org/C30769735</td>\n",
" <td>https://www.wikidata.org/wiki/Q2165951</td>\n",
" <td>3</td>\n",
" <td>0.765911</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI \\\n",
"69 2003 10.1109/VISUAL.2003.1250384 \n",
"\n",
" Title Number of Concepts \\\n",
"69 Acceleration techniques for GPU-based volume r... 16 \n",
"\n",
" Index of Concept Concept Concept ID \\\n",
"69 3 Volume rendering https://openalex.org/C30769735 \n",
"\n",
" Wikidata Level Score \n",
"69 https://www.wikidata.org/wiki/Q2165951 3 0.765911 "
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_L3[vis_L3.Concept == 'Volume rendering'].head(1)"
]
},
{
"cell_type": "markdown",
"id": "8fda3cb1",
"metadata": {},
"source": [
"### VIS L2 & L3"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "a831012f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>concept</th>\n",
" <th>count</th>\n",
" <th>ratio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Visualization</td>\n",
" <td>2266</td>\n",
" <td>0.699</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>Rendering (computer graphics)</td>\n",
" <td>502</td>\n",
" <td>0.155</td>\n",
" </tr>\n",
" <tr>\n",
" <th>49</th>\n",
" <td>Set (abstract data type)</td>\n",
" <td>382</td>\n",
" <td>0.118</td>\n",
" </tr>\n",
" <tr>\n",
" <th>151</th>\n",
" <td>Process (computing)</td>\n",
" <td>345</td>\n",
" <td>0.106</td>\n",
" </tr>\n",
" <tr>\n",
" <th>99</th>\n",
" <td>Context (archaeology)</td>\n",
" <td>261</td>\n",
" <td>0.081</td>\n",
" </tr>\n",
" <tr>\n",
" <th>185</th>\n",
" <td>Analytics</td>\n",
" <td>246</td>\n",
" <td>0.076</td>\n",
" </tr>\n",
" <tr>\n",
" <th>165</th>\n",
" <td>Pattern recognition (psychology)</td>\n",
" <td>212</td>\n",
" <td>0.065</td>\n",
" </tr>\n",
" <tr>\n",
" <th>77</th>\n",
" <td>Domain (mathematical analysis)</td>\n",
" <td>198</td>\n",
" <td>0.061</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>Graph</td>\n",
" <td>158</td>\n",
" <td>0.049</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62</th>\n",
" <td>Focus (optics)</td>\n",
" <td>156</td>\n",
" <td>0.048</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>Graphics</td>\n",
" <td>153</td>\n",
" <td>0.047</td>\n",
" </tr>\n",
" <tr>\n",
" <th>79</th>\n",
" <td>Task (project management)</td>\n",
" <td>149</td>\n",
" <td>0.046</td>\n",
" </tr>\n",
" <tr>\n",
" <th>137</th>\n",
" <td>Field (mathematics)</td>\n",
" <td>147</td>\n",
" <td>0.045</td>\n",
" </tr>\n",
" <tr>\n",
" <th>42</th>\n",
" <td>Cluster analysis</td>\n",
" <td>142</td>\n",
" <td>0.044</td>\n",
" </tr>\n",
" <tr>\n",
" <th>103</th>\n",
" <td>Scalability</td>\n",
" <td>136</td>\n",
" <td>0.042</td>\n",
" </tr>\n",
" <tr>\n",
" <th>97</th>\n",
" <td>Volume (thermodynamics)</td>\n",
" <td>130</td>\n",
" <td>0.040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>121</th>\n",
" <td>Topology (electrical circuits)</td>\n",
" <td>126</td>\n",
" <td>0.039</td>\n",
" </tr>\n",
" <tr>\n",
" <th>94</th>\n",
" <td>Computer graphics</td>\n",
" <td>116</td>\n",
" <td>0.036</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>Computation</td>\n",
" <td>118</td>\n",
" <td>0.036</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>Polygon mesh</td>\n",
" <td>115</td>\n",
" <td>0.035</td>\n",
" </tr>\n",
" <tr>\n",
" <th>41</th>\n",
" <td>Surface (topology)</td>\n",
" <td>113</td>\n",
" <td>0.035</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>Space (punctuation)</td>\n",
" <td>111</td>\n",
" <td>0.034</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>Variety (cybernetics)</td>\n",
" <td>105</td>\n",
" <td>0.032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>223</th>\n",
" <td>Feature (linguistics)</td>\n",
" <td>99</td>\n",
" <td>0.031</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Animation</td>\n",
" <td>100</td>\n",
" <td>0.031</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Point (geometry)</td>\n",
" <td>99</td>\n",
" <td>0.031</td>\n",
" </tr>\n",
" <tr>\n",
" <th>293</th>\n",
" <td>Software</td>\n",
" <td>100</td>\n",
" <td>0.031</td>\n",
" </tr>\n",
" <tr>\n",
" <th>93</th>\n",
" <td>Scalar (mathematics)</td>\n",
" <td>97</td>\n",
" <td>0.030</td>\n",
" </tr>\n",
" <tr>\n",
" <th>219</th>\n",
" <td>Flow (mathematics)</td>\n",
" <td>93</td>\n",
" <td>0.029</td>\n",
" </tr>\n",
" <tr>\n",
" <th>57</th>\n",
" <td>Perception</td>\n",
" <td>90</td>\n",
" <td>0.028</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" concept count ratio\n",
"1 Visualization 2266 0.699\n",
"34 Rendering (computer graphics) 502 0.155\n",
"49 Set (abstract data type) 382 0.118\n",
"151 Process (computing) 345 0.106\n",
"99 Context (archaeology) 261 0.081\n",
"185 Analytics 246 0.076\n",
"165 Pattern recognition (psychology) 212 0.065\n",
"77 Domain (mathematical analysis) 198 0.061\n",
"26 Graph 158 0.049\n",
"62 Focus (optics) 156 0.048\n",
"37 Graphics 153 0.047\n",
"79 Task (project management) 149 0.046\n",
"137 Field (mathematics) 147 0.045\n",
"42 Cluster analysis 142 0.044\n",
"103 Scalability 136 0.042\n",
"97 Volume (thermodynamics) 130 0.040\n",
"121 Topology (electrical circuits) 126 0.039\n",
"94 Computer graphics 116 0.036\n",
"36 Computation 118 0.036\n",
"31 Polygon mesh 115 0.035\n",
"41 Surface (topology) 113 0.035\n",
"9 Space (punctuation) 111 0.034\n",
"61 Variety (cybernetics) 105 0.032\n",
"223 Feature (linguistics) 99 0.031\n",
"3 Animation 100 0.031\n",
"18 Point (geometry) 99 0.031\n",
"293 Software 100 0.031\n",
"93 Scalar (mathematics) 97 0.030\n",
"219 Flow (mathematics) 93 0.029\n",
"57 Perception 90 0.028"
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_l2 = vis[vis.Level == 2]\n",
"vis_l2_concepts = vis_l2.Concept\n",
"vis_l2_dic = dict(Counter(vis_l2_concepts))\n",
"vis_l2_dic_df = pd.DataFrame(vis_l2_dic.items(), columns = ['concept', 'count'])\n",
"vis_l2_dic_df['ratio'] = round(\n",
" vis_l2_dic_df['count'] / len(list(set(vis.DOI))), 3)\n",
"vis_l2_dic_df.sort_values(by = 'ratio', ascending= False).head(30)"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "97015793",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>concept</th>\n",
" <th>count</th>\n",
" <th>ratio</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Data visualization</td>\n",
" <td>1438</td>\n",
" <td>0.444</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>Visual analytics</td>\n",
" <td>486</td>\n",
" <td>0.150</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Information visualization</td>\n",
" <td>388</td>\n",
" <td>0.120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Volume rendering</td>\n",
" <td>273</td>\n",
" <td>0.084</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Representation (politics)</td>\n",
" <td>219</td>\n",
" <td>0.068</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>Interactive visualization</td>\n",
" <td>141</td>\n",
" <td>0.044</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>Scientific visualization</td>\n",
" <td>122</td>\n",
" <td>0.038</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>Isosurface</td>\n",
" <td>104</td>\n",
" <td>0.032</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>Graph drawing</td>\n",
" <td>84</td>\n",
" <td>0.026</td>\n",
" </tr>\n",
" <tr>\n",
" <th>96</th>\n",
" <td>Flow visualization</td>\n",
" <td>77</td>\n",
" <td>0.024</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" concept count ratio\n",
"1 Data visualization 1438 0.444\n",
"18 Visual analytics 486 0.150\n",
"2 Information visualization 388 0.120\n",
"5 Volume rendering 273 0.084\n",
"0 Representation (politics) 219 0.068\n",
"24 Interactive visualization 141 0.044\n",
"32 Scientific visualization 122 0.038\n",
"15 Isosurface 104 0.032\n",
"22 Graph drawing 84 0.026\n",
"96 Flow visualization 77 0.024"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"vis_l3 = vis[vis.Level == 3]\n",
"vis_l3_concepts = vis_l3.Concept\n",
"vis_l3_dic = dict(Counter(vis_l3_concepts))\n",
"vis_l3_dic_df = pd.DataFrame(vis_l3_dic.items(), columns = ['concept', 'count'])\n",
"vis_l3_dic_df['ratio'] = round(\n",
" vis_l3_dic_df['count'] / len(list(set(vis.DOI))), 3)\n",
"vis_l3_dic_df.sort_values(by = 'ratio', ascending= False).head(10)"
]
},
{
"cell_type": "markdown",
"id": "1f609006",
"metadata": {},
"source": [
"## Heat map"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "00c5a529",
"metadata": {},
"outputs": [],
"source": [
"cooccur_orig = pd.read_csv('../data/plots/co_occurrance/aggregated_cooccurance_df.csv')\n",
"sources = cooccur_orig['source']\n",
"targets = cooccur_orig['target']\n",
"values = cooccur_orig['value']\n",
"levels = cooccur_orig['level']\n",
"df2 = pd.DataFrame({\n",
" 'source': targets,\n",
" 'target': sources,\n",
" 'value': values,\n",
" 'level': levels\n",
"})\n",
"cooccur_orig = cooccur_orig.append(df2).reset_index(drop=True)"
]
},
{
"cell_type": "markdown",
"id": "89507c44",
"metadata": {},
"source": [
"### Co-occur in Level 0"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "6ecd8cd0",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>source</th>\n",
" <th>target</th>\n",
" <th>value</th>\n",
" <th>level</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Mathematics</td>\n",
" <td>Computer science</td>\n",
" <td>160</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Computer science</td>\n",
" <td>Physics</td>\n",
" <td>28</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Geology</td>\n",
" <td>Computer science</td>\n",
" <td>23</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Computer science</td>\n",
" <td>Materials science</td>\n",
" <td>15</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Environmental science</td>\n",
" <td>Computer science</td>\n",
" <td>9</td>\n",
" <td>0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" source target value level\n",
"0 Mathematics Computer science 160 0\n",
"1 Computer science Physics 28 0\n",
"2 Geology Computer science 23 0\n",
"3 Computer science Materials science 15 0\n",
"4 Environmental science Computer science 9 0"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cooccur = cooccur_orig[(cooccur_orig.level == 0) & (cooccur_orig.value > 1)]\n",
"cooccur.head()"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "3b7084e6",
"metadata": {},
"outputs": [],
"source": [
"df_wide = cooccur.pivot_table( index='source', columns='target', values='value').fillna(0)"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "4277f705",
"metadata": {},
"outputs": [],
"source": [
"# df_wide = df_wide.replace(\n",
"# ['Artificial intelligence', 'Computer graphics (images)', 'Data science', 'Human-computer interaction', 'Machine learning'],\n",
"# ['AI', 'Computer Graphics', 'DS', 'HCI', 'ML']\n",
"# )"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "1a06f707",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig = plt.figure(figsize=(8, 6))\n",
"g = sns.heatmap(df_wide, cmap=\"YlGnBu\")\n",
"plt.xticks(rotation=88)\n",
"g.set_xlabel('')\n",
"g.set_ylabel('')\n",
"# g.set_title('A', loc = 'left')\n",
"plt.savefig('../results/supp/co_occur_L0.pdf', bbox_inches = 'tight')\n",
"# plt.savefig('../results/figures/heat.png', bbox_inches = 'tight')"
]
},
{
"cell_type": "markdown",
"id": "a319a153",
"metadata": {},
"source": [
"### L1"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "84c284d2",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"cooccur = cooccur_orig[(cooccur_orig.level == 1) & (cooccur_orig.value > 50)]\n",
"cooccur.head()\n",
"df_wide = cooccur.pivot_table( index='source', columns='target', values='value').fillna(0)\n",
"fig = plt.figure(figsize=(8, 6))\n",
"g = sns.heatmap(df_wide, cmap=\"YlGnBu\")\n",
"plt.xticks(rotation=88)\n",
"g.set_xlabel('')\n",
"g.set_ylabel('')\n",
"plt.savefig('../results/supp/co_occur_L1.pdf', bbox_inches = 'tight')"
]
},
{
"cell_type": "markdown",
"id": "1ba6e71c",
"metadata": {},
"source": [
"### L2"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "73af5e15",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"cooccur = cooccur_orig[(cooccur_orig.level == 2) & (cooccur_orig.value > 40)]\n",
"cooccur.head()\n",
"df_wide = cooccur.pivot_table( index='source', columns='target', values='value').fillna(0)\n",
"fig = plt.figure(figsize=(8, 6))\n",
"g = sns.heatmap(df_wide, cmap=\"YlGnBu\")\n",
"plt.xticks(rotation=88)\n",
"g.set_xlabel('')\n",
"g.set_ylabel('')\n",
"plt.savefig('../results/supp/co_occur_L2.pdf', bbox_inches = 'tight')"
]
},
{
"cell_type": "markdown",
"id": "47108ddc",
"metadata": {},
"source": [
"### L3"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "6039378a",
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 576x432 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"cooccur = cooccur_orig[(cooccur_orig.level == 3) & (cooccur_orig.value > 30)]\n",
"cooccur.head()\n",
"df_wide = cooccur.pivot_table( index='source', columns='target', values='value').fillna(0)\n",
"fig = plt.figure(figsize=(8, 6))\n",
"g = sns.heatmap(df_wide, cmap=\"YlGnBu\")\n",
"plt.xticks(rotation=88)\n",
"g.set_xlabel('')\n",
"g.set_ylabel('')\n",
"plt.savefig('../results/supp/co_occur_L3.pdf', bbox_inches = 'tight')"
]
},
{
"cell_type": "markdown",
"id": "fb282fc3",
"metadata": {},
"source": [
"## L1 concept evolution (Stack area chart)\n",
"\n",
"To show the evolution of top ten (and 'Other') Level 1 Concepts of VIS publications over the past 32 years. "
]
},
{
"cell_type": "code",
"execution_count": 60,
"id": "5d1f4317",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Year</th>\n",
" <th>DOI</th>\n",
" <th>Title</th>\n",
" <th>Number of Concepts</th>\n",
" <th>Index of Concept</th>\n",
" <th>Concept</th>\n",
" <th>Concept ID</th>\n",
" <th>Wikidata</th>\n",
" <th>Level</th>\n",
" <th>Score</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>2011</td>\n",
" <td>10.1109/TVCG.2011.185</td>\n",
" <td>D³ Data-Driven Documents</td>\n",
" <td>15</td>\n",
" <td>9</td>\n",
" <td>Programming language</td>\n",
" <td>https://openalex.org/C199360897</td>\n",
" <td>https://www.wikidata.org/wiki/Q9143</td>\n",
" <td>1</td>\n",
" <td>0.489120</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2011</td>\n",
" <td>10.1109/TVCG.2011.185</td>\n",
" <td>D³ Data-Driven Documents</td>\n",
" <td>15</td>\n",
" <td>10</td>\n",
" <td>Information retrieval</td>\n",
" <td>https://openalex.org/C23123220</td>\n",
" <td>https://www.wikidata.org/wiki/Q816826</td>\n",
" <td>1</td>\n",
" <td>0.434999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>2011</td>\n",
" <td>10.1109/TVCG.2011.185</td>\n",
" <td>D³ Data-Driven Documents</td>\n",
" <td>15</td>\n",
" <td>13</td>\n",
" <td>Theoretical computer science</td>\n",
" <td>https://openalex.org/C80444323</td>\n",
" <td>https://www.wikidata.org/wiki/Q2878974</td>\n",
" <td>1</td>\n",
" <td>0.391520</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2011</td>\n",
" <td>10.1109/TVCG.2011.185</td>\n",
" <td>D³ Data-Driven Documents</td>\n",
" <td>15</td>\n",
" <td>14</td>\n",
" <td>Data mining</td>\n",
" <td>https://openalex.org/C124101348</td>\n",
" <td>https://www.wikidata.org/wiki/Q172491</td>\n",
" <td>1</td>\n",
" <td>0.336673</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>2011</td>\n",
" <td>10.1109/TVCG.2011.185</td>\n",
" <td>D³ Data-Driven Documents</td>\n",
" <td>15</td>\n",
" <td>15</td>\n",
" <td>Human–computer interaction</td>\n",
" <td>https://openalex.org/C107457646</td>\n",
" <td>https://www.wikidata.org/wiki/Q207434</td>\n",
" <td>1</td>\n",
" <td>0.325311</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Year DOI Title Number of Concepts \\\n",
"8 2011 10.1109/TVCG.2011.185 D³ Data-Driven Documents 15 \n",
"9 2011 10.1109/TVCG.2011.185 D³ Data-Driven Documents 15 \n",
"12 2011 10.1109/TVCG.2011.185 D³ Data-Driven Documents 15 \n",
"13 2011 10.1109/TVCG.2011.185 D³ Data-Driven Documents 15 \n",
"14 2011 10.1109/TVCG.2011.185 D³ Data-Driven Documents 15 \n",
"\n",
" Index of Concept Concept \\\n",
"8 9 Programming language \n",
"9 10 Information retrieval \n",
"12 13 Theoretical computer science \n",
"13 14 Data mining \n",
"14 15 Human–computer interaction \n",
"\n",
" Concept ID Wikidata \\\n",
"8 https://openalex.org/C199360897 https://www.wikidata.org/wiki/Q9143 \n",
"9 https://openalex.org/C23123220 https://www.wikidata.org/wiki/Q816826 \n",
"12 https://openalex.org/C80444323 https://www.wikidata.org/wiki/Q2878974 \n",
"13 https://openalex.org/C124101348 https://www.wikidata.org/wiki/Q172491 \n",
"14 https://openalex.org/C107457646 https://www.wikidata.org/wiki/Q207434 \n",
"\n",
" Level Score \n",
"8 1 0.489120 \n",
"9 1 0.434999 \n",
"12 1 0.391520 \n",
"13 1 0.336673 \n",
"14 1 0.325311 "
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df = vis\n",
"LEVEL = 1\n",
"level1_df = df[df.Level == LEVEL]\n",
"level1_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "77510564",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Artificial intelligence',\n",
" 'Data mining',\n",
" 'Human–computer interaction',\n",
" 'Computer graphics (images)',\n",
" 'Data science',\n",
" 'Computer vision',\n",
" 'Algorithm',\n",
" 'Theoretical computer science',\n",
" 'Information retrieval',\n",
" 'Machine learning']"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# top ten L1 concepts\n",
"dic = dict(Counter(level1_df.Concept).most_common(10))\n",
"top_ten = list(dic.keys())\n",
"top_ten"
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "8517ac9e",
"metadata": {},
"outputs": [],
"source": [
"# timeseries and rename those concepts not in top ten as \"Other\"\n",
"tuples = []\n",
"for group in level1_df.groupby('Year'):\n",
" year = group[0]\n",
" group[1]['Concept New'] = group[1].Concept.apply(\n",
" lambda x: x if x in top_ten else 'Other'\n",
" )\n",
" for concept_group in group[1].groupby('Concept New'):\n",
" concept = concept_group[0]\n",
" count = concept_group[1].shape[0]\n",
" tuples.append((year, concept, count))"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "16f3eb35",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>year</th>\n",
" <th>concept</th>\n",
" <th>count</th>\n",
" <th>Year</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1990</td>\n",
" <td>Algorithm</td>\n",
" <td>13</td>\n",
" <td>1990-01-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1990</td>\n",
" <td>AI</td>\n",
" <td>14</td>\n",
" <td>1990-01-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1990</td>\n",
" <td>Computer grafics</td>\n",
" <td>28</td>\n",
" <td>1990-01-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1990</td>\n",
" <td>Computer vision</td>\n",
" <td>14</td>\n",
" <td>1990-01-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1990</td>\n",
" <td>Data mining</td>\n",
" <td>2</td>\n",
" <td>1990-01-01</td>\n",
" </tr>\n",
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],
"text/plain": [
" year concept count Year\n",
"0 1990 Algorithm 13 1990-01-01\n",
"1 1990 AI 14 1990-01-01\n",
"2 1990 Computer grafics 28 1990-01-01\n",
"3 1990 Computer vision 14 1990-01-01\n",
"4 1990 Data mining 2 1990-01-01"
]
},
"execution_count": 63,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# prepare for stack area chart\n",
"dff = pd.DataFrame(list(tuples), columns = ['year', 'concept', 'count'])\n",
"dff['Year'] = pd.to_datetime(dff['year'], format='%Y')\n",
"dff.replace({\n",
" 'Artificial intelligence': 'AI',\n",
" 'Human–computer interaction': 'HCI',\n",
" 'Computer graphics (images)': 'Computer grafics'\n",
" \n",
"}, inplace=True)\n",
"dff.head()"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "2b45e3e5",
"metadata": {},
"outputs": [
{
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28, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1990, \"concept\": \"Computer vision\", \"count\": 14, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1990, \"concept\": \"Data mining\", \"count\": 2, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1990, \"concept\": \"Data science\", \"count\": 3, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1990, \"concept\": \"HCI\", \"count\": 11, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1990, \"concept\": \"Information retrieval\", \"count\": 4, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1990, \"concept\": \"Other\", \"count\": 30, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1990, \"concept\": \"Theoretical computer science\", \"count\": 7, \"Year\": \"1990-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Algorithm\", \"count\": 4, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"AI\", \"count\": 16, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Computer grafics\", \"count\": 26, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Computer vision\", \"count\": 12, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Data mining\", \"count\": 5, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Data science\", \"count\": 5, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"HCI\", \"count\": 11, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Information retrieval\", \"count\": 3, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Other\", \"count\": 33, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1991, \"concept\": \"Theoretical computer science\", \"count\": 5, \"Year\": \"1991-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Algorithm\", \"count\": 6, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"AI\", \"count\": 15, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Computer grafics\", \"count\": 29, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Computer vision\", \"count\": 11, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Data mining\", \"count\": 4, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Data science\", \"count\": 4, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"HCI\", \"count\": 8, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Information retrieval\", \"count\": 4, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Other\", \"count\": 40, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1992, \"concept\": \"Theoretical computer science\", \"count\": 2, \"Year\": \"1992-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Algorithm\", \"count\": 5, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"AI\", \"count\": 15, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Computer grafics\", \"count\": 22, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Computer vision\", \"count\": 17, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Data mining\", \"count\": 4, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Data science\", \"count\": 3, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"HCI\", \"count\": 5, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Information retrieval\", \"count\": 4, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Other\", \"count\": 45, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1993, \"concept\": \"Theoretical computer science\", \"count\": 3, \"Year\": \"1993-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Algorithm\", \"count\": 15, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"AI\", \"count\": 10, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Computer grafics\", \"count\": 19, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Computer vision\", \"count\": 9, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Data mining\", \"count\": 4, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Data science\", \"count\": 3, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"HCI\", \"count\": 9, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Information retrieval\", \"count\": 2, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Other\", \"count\": 39, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1994, \"concept\": \"Theoretical computer science\", \"count\": 4, \"Year\": \"1994-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Algorithm\", \"count\": 16, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"AI\", \"count\": 22, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Computer grafics\", \"count\": 22, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Computer vision\", \"count\": 14, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Data mining\", \"count\": 9, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Data science\", \"count\": 6, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"HCI\", \"count\": 19, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Information retrieval\", \"count\": 12, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Other\", \"count\": 47, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1995, \"concept\": \"Theoretical computer science\", \"count\": 8, \"Year\": \"1995-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Algorithm\", \"count\": 17, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"AI\", \"count\": 26, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Computer grafics\", \"count\": 28, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Computer vision\", \"count\": 27, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Data mining\", \"count\": 10, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Data science\", \"count\": 7, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"HCI\", \"count\": 17, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Information retrieval\", \"count\": 7, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Other\", \"count\": 37, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1996, \"concept\": \"Theoretical computer science\", \"count\": 4, \"Year\": \"1996-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Algorithm\", \"count\": 23, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"AI\", \"count\": 27, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Computer grafics\", \"count\": 34, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Computer vision\", \"count\": 17, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Data mining\", \"count\": 19, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Data science\", \"count\": 7, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"HCI\", \"count\": 17, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Information retrieval\", \"count\": 8, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Machine learning\", \"count\": 1, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Other\", \"count\": 43, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1997, \"concept\": \"Theoretical computer science\", \"count\": 10, \"Year\": \"1997-01-01T00:00:00\"}, {\"year\": 1998, \"concept\": \"Algorithm\", \"count\": 23, \"Year\": \"1998-01-01T00:00:00\"}, {\"year\": 1998, \"concept\": \"AI\", \"count\": 31, \"Year\": 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