{"id":2161,"date":"2026-01-15T01:05:28","date_gmt":"2026-01-14T16:05:28","guid":{"rendered":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/?p=2161"},"modified":"2026-01-16T00:42:36","modified_gmt":"2026-01-15T15:42:36","slug":"%e3%81%8a%e3%81%b2%e3%83%a1%e3%83%bc%e3%82%bf%e3%83%bc20260114%e5%ae%9f%e7%b8%be%e9%80%9f%e5%a0%b1","status":"publish","type":"post","link":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/%e3%81%8a%e3%81%b2%e3%83%a1%e3%83%bc%e3%82%bf%e3%83%bc20260114%e5%ae%9f%e7%b8%be%e9%80%9f%e5%a0%b1\/","title":{"rendered":"\u304a\u3072\u30e1\u30fc\u30bf\u30fc20260114\u5b9f\u7e3e\u901f\u5831"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n
2026\/01\/14<\/td>Youtube\u97f3\u6e90\u518d\u751f\u30c7\u30fc\u30bf<\/td>YoutubeMV\u518d\u751f\u30c7\u30fc\u30bf<\/td>USEN\u63a8\u3057\u30ea\u30af<\/td>Spotify\u30d0\u30a4\u30e9\u30eb<\/td>\u5408\u8a08<\/td><\/tr>
<\/td>\u518d\u751f\u6570<\/td>\u3044\u3044\u306d\u6570<\/td>\u30b3\u30e1\u30f3\u30c8\u6570<\/td>\u518d\u751f\u6570<\/td>\u3044\u3044\u306d\u6570<\/td>\u30b3\u30e1\u30f3\u30c8\u6570<\/td>\u9806\u4f4d<\/td>daily20bonus<\/td>\u9806\u4f4d<\/td>daily50bonus<\/td><\/tr>
\u672c\u65e5\u306e\u5b9f\u7e3e<\/td>16985<\/td>90<\/td>6<\/td>77914<\/td>464<\/td>882<\/td><\/td>0<\/td><\/td>0<\/td>–<\/td><\/tr>
\u672c\u65e5\u306e\u304a\u3072\u30e1\u30fc\u30bf\u30fc<\/td>16985<\/td>1800<\/td>600<\/td>77914<\/td>9280<\/td>88200<\/td>0<\/td>–<\/td>0<\/td>–<\/td>19477.9<\/td><\/tr>
\u524d\u65e5\u307e\u3067\u306e\u5b9f\u7e3e<\/td>157910<\/td>2611<\/td>122<\/td>1273162<\/td>35882<\/td>21327<\/td>–<\/td>–<\/td>–<\/td>–<\/td>–<\/td><\/tr>
\u524d\u65e5\u307e\u3067\u306e\u304a\u3072\u30e1\u30fc\u30bf\u30fc<\/td>157910<\/td>52220<\/td>12200<\/td>1273162<\/td>717640<\/td>2132700<\/td><\/td>–<\/td><\/td>–<\/td>434583.2<\/td><\/tr>
\u672c\u65e5\u307e\u3067\u306e\u5b9f\u7e3e<\/td>174895<\/td>2701<\/td>128<\/td>1351076<\/td>36346<\/td>22209<\/td>–<\/td>–<\/td>–<\/td>–<\/td>–<\/td><\/tr>
\u672c\u65e5\u307e\u3067\u306e
\u7d2f\u7a4d\u304a\u3072\u30e1\u30fc\u30bf\u30fc<\/td>		174895<\/td>54020<\/td>12800<\/td>1351076<\/td>726920<\/td>2220900<\/td>0<\/td><\/td>0<\/td><\/td>454061.1<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u30c7\u30fc\u30bf\u30b3\u30e9\u30e0\u9023\u8f09<\/p>\n\n\n\n

Youtube\u30b3\u30e1\u30f3\u30c8\u3092\u5206\u6790\u3059\u308b\u3002<\/h2>\n\n\n\n

\u3000\u304a\u3072\u3055\u307e\u3067\u3043\u3059\u3053\u30fc\u3069\u3067\u306f\u4eca\u30b7\u30f3\u30b0\u30eb\u5411\u3051\u306e\u65b0\u305f\u306a\u53d6\u308a\u7d44\u307f\u3068\u3057\u3066\u300cYoutube\u30b3\u30e1\u30f3\u30c8\u300d\u306e\u5206\u6790\u304b\u3089\u3000\u304a\u3072\u3055\u307e\u304c\u3069\u3093\u306a\u3053\u3068\u306b\u8208\u5473\u3092\u6301\u3063\u3066\u3044\u308b\u306e\u304b\u3092\u5206\u6790\u4e2d\u3067\u3059\u3002<\/p>\n\n\n\n

\u89aa\u30b3\u30e1\u30f3\u30c8\u7d041.8\u4e07\u4ef6\u306e\u30b3\u30e1\u30f3\u30c8\u30c7\u30fc\u30bf\u3092\u3082\u3068\u306bGoogle\u306eColabo\u3092\u6d3b\u7528\u3057\u3001\u30ef\u30fc\u30c9\u30af\u30e9\u30a6\u30c9\u3092\u4f5c\u6210\u3057\u3001\u3069\u3093\u306a\u3053\u3068\u306b\u8208\u5473\u3092\u6301\u3063\u305f\u306e\u304b\u3092\u63a2\u308a\u307e\u3057\u305f\u3002<\/p>\n\n\n\n

\u4f5c\u6210\u3057\u305f\u30ef\u30fc\u30c9\u30af\u30e9\u30a6\u30c9\u3092\u6642\u7cfb\u5217\u3067\u307f\u308b\u3068\u3000\u697d\u66f2\u3084MV\u3067\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u306b\u3064\u3044\u3066\u2192\u6025\u4e0a\u6607\u5165\u308a\u3084\u30df\u30ea\u30aa\u30f3\u5165\u308a\u7b49\u306e\u300c\u5b9f\u7e3e\u300d\u306b\u3064\u3044\u3066\u2192USEN\u63a8\u3057\u30ea\u30af\u7b49\u65e5\u5411\u5742\u3092\u5fdc\u63f4\u306b\u5411\u3051\u305f\u8a71\u306b\u3064\u3044\u3066\u7b49\u5909\u5316\u304c\u898b\u3089\u308c\u307e\u3059\u3002<\/p>\n\n\n\n

\u203b\u30b3\u30fc\u30c9\u4f5c\u6210\u306fGoogle Gemini\u3092\u6d3b\u7528\u3057\u3066\u307e\u3059\u3002<\/p>\n\n\n\n

\u203b\u65e5\u5411\u5742\u3000\u30af\u30ea\u30d5\u30cf\u30f3\u30ac\u30fc\u7b49\u3000\u4e00\u90e8\u30ef\u30fc\u30c9\u3092\u30ce\u30a4\u30ba\u3068\u3057\u3066\u5916\u3057\u3066\u307e\u3059\u3002<\/p>\n\n\n\n

!pip install transformers fugashi ipadic unidic-lite japanize-matplotlib tqdm wordcloud<\/code><\/pre>\n\n\n\n
import pandas as pd\nfrom google.colab import auth\nfrom google.auth import default\nimport gspread\nfrom transformers import pipeline\nimport torch\nimport matplotlib.pyplot as plt\nimport japanize_matplotlib\nfrom tqdm import tqdm\nfrom wordcloud import WordCloud\nimport fugashi\nimport os\n\n# --- \u8a2d\u5b9a ---\nSHEET_URL = '\u30b3\u30e1\u30f3\u30c8\u3092\u53d6\u5f97\u3057\u305fGoogle\u30b9\u30d7\u30ec\u30c3\u30c9\u30b7\u30fc\u30c8\u306eURL'\nTARGET_COLUMN = '\u30b3\u30e1\u30f3\u30c8\u5185\u5bb9'\nDATE_COLUMN = '\u6295\u7a3f\u65e5(JST)'\n\n# \u2605\u3053\u3053\u3067\u9664\u5916\u3057\u305f\u3044\u5358\u8a9e\u3092\u8a2d\u5b9a\u3057\u307e\u3059\nEXCLUDE_WORDS = {'\u65e5\u5411\u5742', '\u65e5\u5411', '\u30af\u30ea\u30d5\u30cf\u30f3\u30ac\u30fc', '\u30af\u30ea\u30d5', '\u30cf\u30f3\u30ac\u30fc', 'MV', '\u5742'}\n# ------------\n\n# 1. Google\u8a8d\u8a3c & \u30c7\u30fc\u30bf\u8aad\u307f\u8fbc\u307f\nprint(\"Google\u8a8d\u8a3c\u3068\u30c7\u30fc\u30bf\u8aad\u307f\u8fbc\u307f\u3092\u884c\u3044\u307e\u3059...\")\nauth.authenticate_user()\ncreds, _ = default()\ngc = gspread.authorize(creds)\nworkbook = gc.open_by_url(SHEET_URL)\nworksheet = workbook.sheet1\nrows = worksheet.get_all_values()\ndf = pd.DataFrame(rows[1:], columns=rows[0])\n\n# 2. \u65e5\u4ed8\u30c7\u30fc\u30bf\u306e\u5909\u63db\nprint(\"\u65e5\u4ed8\u30c7\u30fc\u30bf\u3092\u51e6\u7406\u3057\u3066\u3044\u307e\u3059...\")\ntry:\n    df['datetime'] = pd.to_datetime(df[DATE_COLUMN], errors='coerce')\n    df['date_str'] = df['datetime'].dt.strftime('%Y-%m-%d')\nexcept:\n    pass\n\n# 3. \u5206\u6790\u30e2\u30c7\u30eb\u6e96\u5099\ndevice = 0 if torch.cuda.is_available() else -1\nprint(f\"\u5206\u6790\u30e2\u30c7\u30eb\u3092\u30ed\u30fc\u30c9\u4e2d... (\u30e2\u30fc\u30c9: {'GPU' if device==0 else 'CPU'})\")\nsentiment_analyzer = pipeline(\n    \"sentiment-analysis\",\n    model=\"koheiduck\/bert-japanese-finetuned-sentiment\",\n    tokenizer=\"koheiduck\/bert-japanese-finetuned-sentiment\",\n    device=device\n)\n\n# 4. \u5206\u6790\u5b9f\u884c\ndef analyze_sentiment(text):\n    if not text: return None\n    try:\n        return sentiment_analyzer(str(text)[:512])[0]\n    except:\n        return None\n\nprint(\"\u5168\u30c7\u30fc\u30bf\u306e\u611f\u60c5\u5206\u6790\u3092\u958b\u59cb\u3057\u307e\u3059...\")\ntqdm.pandas()\nresults = df[TARGET_COLUMN].progress_apply(analyze_sentiment)\n\ndf['\u611f\u60c5\u5224\u5b9a'] = results.apply(lambda x: x['label'] if x else None)\nprint(\"\u5206\u6790\u5b8c\u4e86\uff01\")\n\n# --- \u65e5\u5225\u30ef\u30fc\u30c9\u30af\u30e9\u30a6\u30c9\u751f\u6210\uff08\u9664\u5916\u8a2d\u5b9a\u4ed8\u304d\uff09 ---\n\nprint(\"\\n\u30dd\u30b8\u30c6\u30a3\u30d6\u30b3\u30e1\u30f3\u30c8\u306e\u65e5\u5225\u30ef\u30fc\u30c9\u30af\u30e9\u30a6\u30c9\u3092\u4f5c\u6210\u3057\u307e\u3059...\")\n\ntagger = fugashi.Tagger()\ndef extract_nouns(text):\n    if not isinstance(text, str): return \"\"\n    words = []\n    for word in tagger(text):\n        if word.feature.pos1 == '\u540d\u8a5e' and word.feature.pos2 not in ['\u975e\u81ea\u7acb', '\u4ee3\u540d\u8a5e', '\u6570']:\n            words.append(word.surface)\n    return ' '.join(words)\n\nfont_path = os.path.join(os.path.dirname(japanize_matplotlib.__file__), 'fonts', 'ipaexg.ttf')\n\n# \u2605\u8a2d\u5b9a\u306bstopwords\uff08\u9664\u5916\u30ea\u30b9\u30c8\uff09\u3092\u8ffd\u52a0\u3057\u307e\u3057\u305f\nwc_config = {\n    'font_path': font_path,\n    'width': 600, 'height': 400,\n    'background_color': 'white',\n    'regexp': r\"[\\w']+\",\n    'colormap': 'spring',\n    'collocations': False,\n    'stopwords': EXCLUDE_WORDS  # \u2190 \u3053\u3053\u3067\u9664\u5916\u30ea\u30b9\u30c8\u3092\u9069\u7528\n}\n\npositive_df = df[df['\u611f\u60c5\u5224\u5b9a'] == 'POSITIVE'].copy()\ngrouped = positive_df.groupby('date_str')\ntarget_dates = sorted(positive_df['date_str'].dropna().unique())\n\nif target_dates:\n    MAX_DAYS = 20\n    if len(target_dates) > MAX_DAYS:\n        print(f\"\u203b\u65e5\u6570\u304c\u591a\u3044\u305f\u3081\u3001\u30b3\u30e1\u30f3\u30c8\u6570\u304c\u591a\u3044\u4e0a\u4f4d {MAX_DAYS} \u65e5\u5206\u3092\u8868\u793a\u3057\u307e\u3059\u3002\")\n        top_dates = positive_df['date_str'].value_counts().nlargest(MAX_DAYS).index\n        target_dates = sorted(top_dates)\n\n    for date in target_dates:\n        day_comments = grouped.get_group(date)[TARGET_COLUMN]\n        full_text = \" \".join(day_comments.astype(str))\n        nouns = extract_nouns(full_text)\n        \n        # \u9664\u5916\u5f8c\u306e\u5358\u8a9e\u6570\u304c\u5c11\u306a\u3044\u5834\u5408\u306f\u30b9\u30ad\u30c3\u30d7\u3059\u308b\u51e6\u7406\n        # (WordCloud\u5185\u90e8\u3067\u3082\u9664\u5916\u3055\u308c\u307e\u3059\u304c\u3001\u5ff5\u306e\u305f\u3081\u751f\u6210\u524d\u306b\u30c1\u30a7\u30c3\u30af)\n        if len(nouns) < 10: continue\n\n        wc = WordCloud(**wc_config).generate(nouns)\n        \n        plt.figure(figsize=(8, 5))\n        plt.imshow(wc, interpolation='bilinear')\n        plt.title(f'{date} \u306e\u30dd\u30b8\u30c6\u30a3\u30d6\u30ef\u30fc\u30c9', fontsize=16)\n        plt.axis('off')\n        plt.show()\n\nprint(\"\u5168\u51e6\u7406\u304c\u5b8c\u4e86\u3057\u307e\u3057\u305f\u3002\")<\/code><\/pre>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n","protected":false},"excerpt":{"rendered":"
2026\/01\/14 Youtube\u97f3\u6e90\u518d\u751f\u30c7\u30fc\u30bf YoutubeMV\u518d\u751f\u30c7\u30fc\u30bf USEN\u63a8\u3057\u30ea\u30af Spotify\u30d0\u30a4\u30e9\u30eb \u5408\u8a08 \u518d\u751f\u6570 \u3044\u3044\u306d\u6570 \u30b3\u30e1\u30f3\u30c8\u6570 \u518d\u751f\u6570 \u3044\u3044\u306d\u6570 \u30b3\u30e1\u30f3\u30c8\u6570 \u9806\u4f4d daily20bonus […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[37],"tags":[],"class_list":["post-2161","post","type-post","status-publish","format-standard","hentry","category-ohi-meter"],"_links":{"self":[{"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/posts\/2161","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/comments?post=2161"}],"version-history":[{"count":5,"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/posts\/2161\/revisions"}],"predecessor-version":[{"id":2187,"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/posts\/2161\/revisions\/2187"}],"wp:attachment":[{"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/media?parent=2161"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/categories?post=2161"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tsuka-radio.conohawing.com\/ohisama\/wp-json\/wp\/v2\/tags?post=2161"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}