First Version

2026-06-27 07:52:17 +03:30
commit f3d28cea99
97 changed files with 54562 additions and 0 deletions
@@ -0,0 +1,107 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "0e4e4b7d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import json\n",
+    "with open('Step3_output_article_response_original_3.json', encoding=\"utf8\") as f:\n",
+    "    data_pos = json.load(f)\n",
+    "with open('Step3_output_article_response_opposite_2.json', encoding=\"utf8\") as f:\n",
+    "    data_neg = json.load(f)\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "e7b83fa4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "combined_list = []\n",
+    "for art_id in range(len(data_pos)):\n",
+    "    entry = {}\n",
+    "    entry['article_id'] = art_id\n",
+    "    entry['article_name'] = data_pos[art_id]['title']\n",
+    "    entry['article_institute'] = data_pos[art_id]['universities']\n",
+    "    entry['article_abstract'] = data_pos[art_id]['abstract']\n",
+    "    \n",
+    "    entry['measures_positive'] = [l[0] for l in data_pos[art_id]['response'][0][:]]\n",
+    "    entry['responses_positive'] = [l[2] for l in data_pos[art_id]['response'][0][:]]\n",
+    "    entry['scores_positive'] = [l[3] for l in data_pos[art_id]['response'][0][:]]\n",
+    "    \n",
+    "    entry['measures_negative'] = [l[0] for l in data_neg[art_id]['response'][0][:]]\n",
+    "    entry['responses_negative'] = [l[2] for l in data_neg[art_id]['response'][0][:]]\n",
+    "    entry['scores_negative'] = [l[3] for l in data_neg[art_id]['response'][0][:]]\n",
+    "\n",
+    "    combined_list += [entry]\n",
+    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "24d0c9b5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('output/Step4_article_response_all_combined_2.json', 'w', encoding=\"utf8\") as f:\n",
+    "    json.dump(combined_list, f, ensure_ascii=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "0cda7716",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import csv\n",
+    "\n",
+    "def write_csv(filename, score_lbl='scores_positive'):\n",
+    "    # Open the file in append mode\n",
+    "    with open(filename, mode='w', newline='', encoding=\"utf-8-sig\") as file:\n",
+    "        writer = csv.writer(file)\n",
+    "\n",
+    "        labels = ['Value '+str(j) for j in range(64)]\n",
+    "\n",
+    "        writer.writerow(['Institute'] + labels)\n",
+    "\n",
+    "        for i in range(0, len(combined_list)):\n",
+    "            article = combined_list[i]\n",
+    "            uni = article['article_institute']\n",
+    "            rankings = article[score_lbl]\n",
+    "            writer.writerow([uni]+rankings)\n",
+    "            \n",
+    "write_csv(filename='output/Step4_scores_positive_2.csv', score_lbl='scores_positive')\n",
+    "write_csv(filename='output/Step4_scores_negative_2.csv', score_lbl='scores_negative')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.12.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}