月刊文藝春秋（文藝春秋 電子版）
芥川賞受賞作を全文掲載する月刊誌「文藝春秋」の公式アカウント。記事をTwitterで毎日お届けします。本誌特集記事が雑誌よりも早く読める、月10本開催の対談イベントが見放題のサブスク「文藝春秋 電子版」はこちら（新規登録は「月あたり450円」から）→ https://bunshun.jp/bungeishunju
91,788
Followers
8,584
Following
26,038
Tweets
36.4
Avg Engagement
1,027
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @gekkan_bunshun's Twitter/X presence across multiple dimensions. We analyze tweet content, engagement patterns, audience demographics, posting habits, and network connections to provide actionable insights about this account's social media strategy and influence.
Account Classification
- Account Size: Mid-Tier (10K+)
- Account Age:2010-06-30
- Verification:No
- Location:東京都千代田区紀尾井町
Data Summary
- Tweets Analyzed:3,248
- Avg Likes per Tweet:17.5
- Avg Retweets per Tweet:18.9
- Followers Analyzed:10,999
Engagement Analysis
Based on 3,248 tweets推文平均獲得約1,915個喜歡和662個轉發，顯示其內容具有一定的互動性。推文主題多與熱門話題相關，有助於提高參與度。
17.5
Avg Likes/Tweet
18.9
Avg Retweets/Tweet
57,002
Total Likes
61,251
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
5
Median Likes
1
Median Retweets
13
75th Percentile
6,098
Top Tweet
0.4
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Broadcaster
Primarily shares original content
77.9%
Original
10.0%
Replies
12.0%
Retweets
0.0%
Quotes
0.0%
Threads
0.0%
With Media
99.2%
With Links
76.6%
With #Tags
22.3%
With @Mentions
13.2%
With Emojis
119
Avg Length
Audience Reaction Profile
Broadcast
Focuses on original content over replies
0.13
Reply/Original Ratio
0.0
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
73.7%
Weekday Posts
26.3%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,248 tweetsContent Type Distribution
Content Breakdown
What This Reveals About Their Strategy
This is a content-creator focused account that primarily shares original thoughts, ideas, and media. With original content dominating their feed, they position themselves as a source of new information rather than a curator. This strategy works well for establishing thought leadership.
The 391 retweets (12% of activity) show they also amplify content from others, which helps build relationships with other accounts and provides value to followers by surfacing relevant content.
Posting Patterns & Optimal Timing
Based on 3,248 tweetsEngagement by Hour (UTC)
Posting Frequency Over Time
Timing Insights
Understanding when an account posts and when their audience is most responsive provides valuable competitive intelligence. The charts above show when this account's content receives the most engagement, which often correlates with when their specific audience is most active on the platform.
Peak posting times vary significantly based on an account's audience demographics, timezone distribution, and content type. Accounts with global audiences often see engagement spread across multiple time windows, while those with regional focus may have more concentrated peaks.
Audience Demographics
Based on 10,999 followers主要觀眾為對日本文學、娛樂圈及時事感興趣的讀者。他們可能對芥川賞得獎作品、藝人動向及媒體報導有較高的關注度。
Average
Audience Quality
22.0%
Suspicion Index
28.0%
Low-Quality %
57
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
39.1%
Empty Bio
24.4%
<10 Tweets
13.6%
Mass Following (>2K)
0.0%
New (<90 days)
40.8%
Low Ratio (<0.1)
0.0%
New (<180 days)
85.8%
No URL
16.9%
<3 Tweets
Free Mode Analysis: These quality metrics use heuristic signals (empty bios, low tweets, suspicious ratios). For ML-powered bot detection with 95%+ accuracy, use our dedicated tool.
Try Bot DetectorFollower Reach & Influence
This account's followers have their own audiences, creating potential for secondary amplification.
7,920,804
Total Potential Reach
57
Median Follower Reach
288
75th Percentile Reach
9.4%
>1K followers
0.7%
>10K followers
0.1%
>50K followers
0.0%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
59.1%
Creators
6,495 accounts
16.6%
Consumers
1,822 accounts
24.4%
Dormant
2,682 accounts
Follower Influence Distribution
How many followers do their followers have?
Follower Account Age
How long have followers been on Twitter?
Geographic Distribution
Top locations where followers are based (from those who share location data):
104
Verified Followers
0.95% of total
1,207
Protected Accounts
10.97% of total
5 years
Avg Account Age
of their followers
Notable Followers (By Influence)
Top accounts following this user, sorted by their follower count:
| Username | Followers | Profession | Interests |
|---|---|---|---|
| @UNIQLO_JP | 1,608,265 | Retail | Fashion, Deals, Customer Service |
| @nekokumicho | 256,244 | Author | cats, economics, criticism |
| @AKIHIRONAMBA | 186,288 | Musician | Hi-STANDARD, 新潟ラーメン, COREMANIA |
| @daisuke_higedan | 147,101 | Musician | Pop, Punk, Guitar |
| @HANADA_asuka | 123,697 | - | - |
| @shueishabunko | 91,911 | Publisher | Books, Campaigns, Recommendations |
| @sadycork | 72,933 | Editor | Manga, Editing, YouTube |
| @sm_hn | 69,679 | Tech Journalist | Mobile, 5G, Technology |
| @doshisha_marche | 64,913 | E-commerce | kitchenware, appliances, outdoor gear |
| @heihachiro888 | 62,781 | - | - |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
6,698
Followers With Bio
4,301
Followers Without Bio
60.9%
% With Bio
39.1%
% Without Bio
Why Audience Demographics Matter
Understanding who follows an account reveals the type of influence they hold. Accounts followed primarily by users with few followers indicate broad, mainstream appeal. Those with many high-follower followers have greater potential for content amplification through secondary sharing.
Account age distribution also tells a story: a follower base with many new accounts might indicate recent viral growth, while established followers suggest long-term, stable influence. Geographic data helps understand the cultural context and timezone spread of the audience.
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Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,248 analyzed20,413
Combined Engagement
9,522
Total Likes
10,891
Total Retweets
4,083
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
60%
With Hashtags
40%
With @Mentions
100%
With Links
Topical Analysis:
SMAPの“公開謝罪番組”を担当した放送作家、鈴木おさむ氏の小説「20160118」が大きな話題を呼んでいる。いまジャニーズ事務所で何が起きているのか。 https://t.co/Zo4gphCSOM #ジャニーズ事務所 #芸能人
《SMAPのいちばん長い日が小説に》担当放送作家が小説として執筆 “20160118“生放送の現場 「文藝春秋」編集部 https://t.co/cJ3TpJKBK9
RT @product1954: 東京国立博物館の館長「このままでは国宝を守れない。光熱費不足分を補正予算に盛り込んで欲しいと文化庁に要望したが、ゼロ査定だった」 一方、北京や平壌を攻撃するトマホーク500発購入、国民管理強化のマイナカード普及のカネは惜しまない岸田政権 #新しい戦前にさせない https://t.co/4PQMyL7TCT
RT @masaki_kito: DIA報告書「1991年に4500億円、1993年に300万ドルの寄贈を行った後、北朝鮮は統一教会との関係を確立した」という詳細な記述。教団が日本の信者たちから集めた献金が韓国、香港経由で北朝鮮に渡り、それが核やICBMの開発に使われた可能性>9日発売の「文藝春秋」（1月号） https://t.co/L3dS973lsA
「“辞めジャニ”をキャスティングすれば、事務所から“出禁”となり、他の作品にジャニーズの人気タレントが出てくれなくなるかもしれない。そのリスクを避けるため、過剰な忖度が働き、結果的に独立組を排除しています」（広告代理店幹部社員） https://t.co/fxWyIbv9oJ #テレビ #辞めジャニ
Key Insights & Takeaways
帳號內容與日本娛樂圈及時事緊密相關，吸引大量關注 推文多與熱門事件或爭議性話題有關，提高互動率 帳號積極推廣其電子版訂閱服務，並透過推文提高曝光度
Strengths
- + Established follower base of 91,788
- + Strong original content creation
- + Active presence with consistent posting
Opportunities
- ~ Optimize posting times for peak engagement windows
- ~ Analyze top-performing content for replicable patterns
- ~ Leverage geographic concentration for targeted content
- ~ Explore collaboration potential with followed accounts
Summary
This analysis of @gekkan_bunshun reveals an growing Twitter presence with 91,788 followers. The account demonstrates a content-creator strategy, averaging 36.4 engagements per tweet. Key strengths include consistent posting and an engaged audience, with opportunities to further optimize timing and content strategy based on the patterns identified in this report.
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