remove negative words

words_syllables.ipynb

@@ -238,6 +238,54 @@
     "    writer = csv.writer(csvfile)\n",
     "    writer.writerows(single_syllable_nouns_cleaned)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "836b0473-2b4f-4c82-921e-1d6ed51c65f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from textblob import TextBlob\n",
+    "\n",
+    "# Alternative method using sentiment analysis (requires: pip install textblob)\n",
+    "def is_negative(word):\n",
+    "    # Simple sentiment check - words with negative polarity\n",
+    "    analysis = TextBlob(word)\n",
+    "    return analysis.sentiment.polarity < -0.1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "1c9517b7-a17a-4c94-9bd6-ca0da1cfd708",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "cow\n",
+      "game\n",
+      "green\n"
+     ]
+    }
+   ],
+   "source": [
+    "for word in single_syllable_nouns_cleaned:\n",
+    "    if is_negative(word):\n",
+    "        print(word)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "3a2e6440-842c-4a2f-be1e-49b4771c651b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sentiment_filtered_nouns = [word for word in single_syllable_nouns_cleaned if not is_negative(word)]"
+   ]
   }
  ],
  "metadata": {