573 lines
18 KiB
Plaintext
573 lines
18 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 1,
|
||
"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>root</th>\n",
|
||
" <th>mean_ranking</th>\n",
|
||
" <th>std_ranking</th>\n",
|
||
" <th>word_matches</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>challeng</td>\n",
|
||
" <td>420</td>\n",
|
||
" <td>264</td>\n",
|
||
" <td>['challenges', 'challenge', 'challenging']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>SDG</td>\n",
|
||
" <td>423</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>['sdgs']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>ESG</td>\n",
|
||
" <td>636</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>['esg']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>recycling</td>\n",
|
||
" <td>860</td>\n",
|
||
" <td>154</td>\n",
|
||
" <td>['recycling', 'shiprecycling']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>reduc</td>\n",
|
||
" <td>1242</td>\n",
|
||
" <td>965</td>\n",
|
||
" <td>['reduce', 'reducing', 'reduced', 'reduction',...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>5</th>\n",
|
||
" <td>planet</td>\n",
|
||
" <td>1295</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>['planet']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>6</th>\n",
|
||
" <td>CSR</td>\n",
|
||
" <td>1371</td>\n",
|
||
" <td>0</td>\n",
|
||
" <td>['csr']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>7</th>\n",
|
||
" <td>sustainab</td>\n",
|
||
" <td>1527</td>\n",
|
||
" <td>1873</td>\n",
|
||
" <td>['sustainability', 'sustainable', 'sustainable...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>8</th>\n",
|
||
" <td>clean</td>\n",
|
||
" <td>1695</td>\n",
|
||
" <td>837</td>\n",
|
||
" <td>['theoceancleanup', 'cleanup', 'clean', 'clean...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>9</th>\n",
|
||
" <td>methanol</td>\n",
|
||
" <td>1700</td>\n",
|
||
" <td>1044</td>\n",
|
||
" <td>['methanol', 'emethanol']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>10</th>\n",
|
||
" <td>future</td>\n",
|
||
" <td>1770</td>\n",
|
||
" <td>1684</td>\n",
|
||
" <td>['future', 'futureproofing']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>11</th>\n",
|
||
" <td>garbage</td>\n",
|
||
" <td>1808</td>\n",
|
||
" <td>612</td>\n",
|
||
" <td>['garbage', 'greatpacificgarbagepatch']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>12</th>\n",
|
||
" <td>responsib</td>\n",
|
||
" <td>1889</td>\n",
|
||
" <td>1135</td>\n",
|
||
" <td>['responsible', 'responsibility', 'responsibly...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>13</th>\n",
|
||
" <td>carb</td>\n",
|
||
" <td>1952</td>\n",
|
||
" <td>1526</td>\n",
|
||
" <td>['decarbonisation', 'carbon', 'decarbonization...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>14</th>\n",
|
||
" <td>chang</td>\n",
|
||
" <td>2148</td>\n",
|
||
" <td>1667</td>\n",
|
||
" <td>['change', 'changing', 'climatechange', 'chang...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>15</th>\n",
|
||
" <td>ocean</td>\n",
|
||
" <td>2169</td>\n",
|
||
" <td>1629</td>\n",
|
||
" <td>['ocean', 'theoceancleanup', 'oceans', 'oceanp...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>16</th>\n",
|
||
" <td>plastic</td>\n",
|
||
" <td>2320</td>\n",
|
||
" <td>1490</td>\n",
|
||
" <td>['plastic', 'oceanplastic', 'plasticwaste', 'p...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>17</th>\n",
|
||
" <td>neutral</td>\n",
|
||
" <td>2382</td>\n",
|
||
" <td>1798</td>\n",
|
||
" <td>['neutral', 'carbonneutral', 'neutrality', 'co...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>18</th>\n",
|
||
" <td>environment</td>\n",
|
||
" <td>2391</td>\n",
|
||
" <td>1574</td>\n",
|
||
" <td>['environment', 'environmental', 'unenvironmen...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>19</th>\n",
|
||
" <td>green</td>\n",
|
||
" <td>2393</td>\n",
|
||
" <td>1158</td>\n",
|
||
" <td>['green', 'greenfuels', 'greener', 'greenfuel'...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>20</th>\n",
|
||
" <td>sulphur</td>\n",
|
||
" <td>2828</td>\n",
|
||
" <td>1772</td>\n",
|
||
" <td>['sulphur', 'lowsulphur']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>21</th>\n",
|
||
" <td>emissions</td>\n",
|
||
" <td>2925</td>\n",
|
||
" <td>2046</td>\n",
|
||
" <td>['emissions', 'carbonemissions', 'zeroemissions']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>22</th>\n",
|
||
" <td>zero</td>\n",
|
||
" <td>2977</td>\n",
|
||
" <td>1646</td>\n",
|
||
" <td>['zero', 'netzero', 'zerocarbon', 'zerocarbons...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>23</th>\n",
|
||
" <td>climate</td>\n",
|
||
" <td>3046</td>\n",
|
||
" <td>2095</td>\n",
|
||
" <td>['climateaction', 'climate', 'climatechange', ...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>24</th>\n",
|
||
" <td>eco</td>\n",
|
||
" <td>3074</td>\n",
|
||
" <td>1269</td>\n",
|
||
" <td>['ecosystem', 'eco', 'maerskecodelivery', 'eco...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>25</th>\n",
|
||
" <td>mission</td>\n",
|
||
" <td>3247</td>\n",
|
||
" <td>1950</td>\n",
|
||
" <td>['emissions', 'mission', 'eucommission', 'carb...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>26</th>\n",
|
||
" <td>CO2</td>\n",
|
||
" <td>3390</td>\n",
|
||
" <td>2275</td>\n",
|
||
" <td>['co2', 'co2neutral', 'co2emission']</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>27</th>\n",
|
||
" <td>bio</td>\n",
|
||
" <td>3687</td>\n",
|
||
" <td>1274</td>\n",
|
||
" <td>['biofuel', 'biofuels', 'biohuts', 'biodiversi...</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" root mean_ranking std_ranking \n",
|
||
"0 challeng 420 264 \\\n",
|
||
"1 SDG 423 0 \n",
|
||
"2 ESG 636 0 \n",
|
||
"3 recycling 860 154 \n",
|
||
"4 reduc 1242 965 \n",
|
||
"5 planet 1295 0 \n",
|
||
"6 CSR 1371 0 \n",
|
||
"7 sustainab 1527 1873 \n",
|
||
"8 clean 1695 837 \n",
|
||
"9 methanol 1700 1044 \n",
|
||
"10 future 1770 1684 \n",
|
||
"11 garbage 1808 612 \n",
|
||
"12 responsib 1889 1135 \n",
|
||
"13 carb 1952 1526 \n",
|
||
"14 chang 2148 1667 \n",
|
||
"15 ocean 2169 1629 \n",
|
||
"16 plastic 2320 1490 \n",
|
||
"17 neutral 2382 1798 \n",
|
||
"18 environment 2391 1574 \n",
|
||
"19 green 2393 1158 \n",
|
||
"20 sulphur 2828 1772 \n",
|
||
"21 emissions 2925 2046 \n",
|
||
"22 zero 2977 1646 \n",
|
||
"23 climate 3046 2095 \n",
|
||
"24 eco 3074 1269 \n",
|
||
"25 mission 3247 1950 \n",
|
||
"26 CO2 3390 2275 \n",
|
||
"27 bio 3687 1274 \n",
|
||
"\n",
|
||
" word_matches \n",
|
||
"0 ['challenges', 'challenge', 'challenging'] \n",
|
||
"1 ['sdgs'] \n",
|
||
"2 ['esg'] \n",
|
||
"3 ['recycling', 'shiprecycling'] \n",
|
||
"4 ['reduce', 'reducing', 'reduced', 'reduction',... \n",
|
||
"5 ['planet'] \n",
|
||
"6 ['csr'] \n",
|
||
"7 ['sustainability', 'sustainable', 'sustainable... \n",
|
||
"8 ['theoceancleanup', 'cleanup', 'clean', 'clean... \n",
|
||
"9 ['methanol', 'emethanol'] \n",
|
||
"10 ['future', 'futureproofing'] \n",
|
||
"11 ['garbage', 'greatpacificgarbagepatch'] \n",
|
||
"12 ['responsible', 'responsibility', 'responsibly... \n",
|
||
"13 ['decarbonisation', 'carbon', 'decarbonization... \n",
|
||
"14 ['change', 'changing', 'climatechange', 'chang... \n",
|
||
"15 ['ocean', 'theoceancleanup', 'oceans', 'oceanp... \n",
|
||
"16 ['plastic', 'oceanplastic', 'plasticwaste', 'p... \n",
|
||
"17 ['neutral', 'carbonneutral', 'neutrality', 'co... \n",
|
||
"18 ['environment', 'environmental', 'unenvironmen... \n",
|
||
"19 ['green', 'greenfuels', 'greener', 'greenfuel'... \n",
|
||
"20 ['sulphur', 'lowsulphur'] \n",
|
||
"21 ['emissions', 'carbonemissions', 'zeroemissions'] \n",
|
||
"22 ['zero', 'netzero', 'zerocarbon', 'zerocarbons... \n",
|
||
"23 ['climateaction', 'climate', 'climatechange', ... \n",
|
||
"24 ['ecosystem', 'eco', 'maerskecodelivery', 'eco... \n",
|
||
"25 ['emissions', 'mission', 'eucommission', 'carb... \n",
|
||
"26 ['co2', 'co2neutral', 'co2emission'] \n",
|
||
"27 ['biofuel', 'biofuels', 'biohuts', 'biodiversi... "
|
||
]
|
||
},
|
||
"execution_count": 1,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# load words related to sustainability\n",
|
||
"import pandas as pd\n",
|
||
"\n",
|
||
"path = 'word_root_ranking.csv'\n",
|
||
"df = pd.read_csv(path, index_col=0)\n",
|
||
"\n",
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"['challenges',\n",
|
||
" 'challenge',\n",
|
||
" 'challenging',\n",
|
||
" 'sdgs',\n",
|
||
" 'esg',\n",
|
||
" 'recycling',\n",
|
||
" 'shiprecycling',\n",
|
||
" 'reduce',\n",
|
||
" 'reducing',\n",
|
||
" 'reduced']"
|
||
]
|
||
},
|
||
"execution_count": 2,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# collect words into list\n",
|
||
"\n",
|
||
"related_words_list = list()\n",
|
||
"for row in df['word_matches']:\n",
|
||
" word_list = row.strip('][').replace(\"'\", '').split(', ')\n",
|
||
" for word in word_list:\n",
|
||
" related_words_list.append(word)\n",
|
||
" \n",
|
||
"related_words_list[:10]"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"1511"
|
||
]
|
||
},
|
||
"execution_count": 19,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# load in all tweet texts\n",
|
||
"from pathlib import Path\n",
|
||
"import re\n",
|
||
"\n",
|
||
"tweet_dir = Path('tweets').resolve()\n",
|
||
"path_list = list(tweet_dir.glob('*.txt'))\n",
|
||
"score_list = list()\n",
|
||
"for path in path_list:\n",
|
||
" with open(path, 'r') as f:\n",
|
||
" text = f.read()\n",
|
||
" text = re.search(\n",
|
||
" pattern='(?<=text: )(.|\\n)*(?=images: )',\n",
|
||
" string=text\n",
|
||
" ).group(0)\n",
|
||
" score = sum([related_word in text for related_word in related_words_list])\n",
|
||
" score_list.append(score)\n",
|
||
"\n",
|
||
"len(score_list)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"15"
|
||
]
|
||
},
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"max(score_list)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 25,
|
||
"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>path</th>\n",
|
||
" <th>score</th>\n",
|
||
" </tr>\n",
|
||
" </thead>\n",
|
||
" <tbody>\n",
|
||
" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2021-08-24-0...</td>\n",
|
||
" <td>15</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2021-06-22-1...</td>\n",
|
||
" <td>14</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2020-07-13-1...</td>\n",
|
||
" <td>14</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2022-04-28-1...</td>\n",
|
||
" <td>13</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2022-10-20-1...</td>\n",
|
||
" <td>13</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1506</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2022-08-31-1...</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1507</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2022-12-17-0...</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1508</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2021-09-24-0...</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1509</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2014-02-06-1...</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1510</th>\n",
|
||
" <td>/home/brian/solveig_master/tweets/2017-10-12-1...</td>\n",
|
||
" <td>0</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>1511 rows × 2 columns</p>\n",
|
||
"</div>"
|
||
],
|
||
"text/plain": [
|
||
" path score\n",
|
||
"0 /home/brian/solveig_master/tweets/2021-08-24-0... 15\n",
|
||
"1 /home/brian/solveig_master/tweets/2021-06-22-1... 14\n",
|
||
"2 /home/brian/solveig_master/tweets/2020-07-13-1... 14\n",
|
||
"3 /home/brian/solveig_master/tweets/2022-04-28-1... 13\n",
|
||
"4 /home/brian/solveig_master/tweets/2022-10-20-1... 13\n",
|
||
"... ... ...\n",
|
||
"1506 /home/brian/solveig_master/tweets/2022-08-31-1... 0\n",
|
||
"1507 /home/brian/solveig_master/tweets/2022-12-17-0... 0\n",
|
||
"1508 /home/brian/solveig_master/tweets/2021-09-24-0... 0\n",
|
||
"1509 /home/brian/solveig_master/tweets/2014-02-06-1... 0\n",
|
||
"1510 /home/brian/solveig_master/tweets/2017-10-12-1... 0\n",
|
||
"\n",
|
||
"[1511 rows x 2 columns]"
|
||
]
|
||
},
|
||
"execution_count": 25,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"df = pd.DataFrame(\n",
|
||
" {\n",
|
||
" 'path': path_list,\n",
|
||
" 'score': score_list\n",
|
||
" }\n",
|
||
")\n",
|
||
"\n",
|
||
"df = df.sort_values(by='score', ascending=False)\n",
|
||
"df.reset_index(drop=True, inplace=True)\n",
|
||
"df"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 27,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"df.to_csv('tweets_relevance_list.csv')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": []
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "venv",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.8.10"
|
||
},
|
||
"orig_nbformat": 4
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|