AORUS (JP)
GIGABYTE の日本公式アカウントです。 AORUS (オーラス) や AERO (エアロ) など、色々な製品を展開しております。 ・製品のお問い合せは、各サポート窓口までお願いいたします → https://www.gigabyte.com/jp/Support/Warranty ・AORUS TV (YouTube) → https://www.youtube.com/channel/UC_eOB5VkrArQABvGHhThsvA
87,834
Followers
5,782
Following
26,605
Tweets
66.7
Avg Engagement
727
Listed
No
Verified
Account Overview
What This Report Covers
This comprehensive analysis examines @AORUS_JP'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:2016-06-29
- Verification:No
- Location:日本
Data Summary
- Tweets Analyzed:3,239
- Avg Likes per Tweet:22.6
- Avg Retweets per Tweet:44.1
- Followers Analyzed:10,000
Engagement Analysis
Based on 3,239 tweets账号通过抽奖和互动活动保持较高的参与度，平均点赞和转发数均较高。用户积极参与抽奖和评论，显示出对品牌活动的浓厚兴趣。
22.6
Avg Likes/Tweet
44.1
Avg Retweets/Tweet
73,183
Total Likes
142,886
Total Retweets
Engagement Quality Analysis
Median-based metrics that resist fake virality and outliers.
0
Median Likes
4
Median Retweets
33
75th Percentile
12,125
Top Tweet
0.76
Engagement per 1K Followers
Normalized influence metric
Viral Spikes
Engagement Pattern
Few posts get most engagement
Posting Behavior
Content style and format preferences
Curator
Amplifies others content frequently
23.1%
Original
8.1%
Replies
57.7%
Retweets
11.1%
Quotes
0.0%
Threads
0.0%
With Media
93.7%
With Links
22.6%
With #Tags
63.1%
With @Mentions
22.9%
With Emojis
130
Avg Length
Audience Reaction Profile
Interactive
Balances broadcasting with conversation
0.35
Reply/Original Ratio
0.19
Quote/RT Ratio
Posting Rhythm
Somewhat Bursty
Occasional posting spikes
76.3%
Weekday Posts
23.7%
Weekend Posts
Top Hashtags
Most Mentioned
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Content Strategy Analysis
Based on 3,239 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 1,870 retweets (58% 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 3,239 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 10,000 followers主要受众为对游戏硬件和电脑配件感兴趣的用户，尤其是游戏玩家和科技爱好者。用户群体可能包括年轻男性和有一定技术背景的消费者。
Good
Audience Quality
19.4%
Suspicion Index
15.1%
Low-Quality %
59
Median Reach
Audience Quality Signals
Lower percentages indicate healthier, more authentic followers.
27.7%
Empty Bio
4.2%
<10 Tweets
21.1%
Mass Following (>2K)
0.0%
New (<90 days)
51.5%
Low Ratio (<0.1)
0.0%
New (<180 days)
87.8%
No URL
2.5%
<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.
4,574,543
Total Potential Reach
59
Median Follower Reach
207
75th Percentile Reach
6.3%
>1K followers
0.5%
>10K followers
0.1%
>50K followers
0.1%
>100K followers
Creator vs Consumer Split
Classification based on tweet activity: Creators (>100 tweets), Consumers (10-100 tweets), Dormant (<10 tweets).
86.2%
Creators
8,618 accounts
9.6%
Consumers
964 accounts
4.2%
Dormant
418 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):
51
Verified Followers
0.51% of total
261
Protected Accounts
2.61% of total
4 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 |
|---|---|---|---|
| @fukuenomajinai | 349,685 | Astrologer | 復縁, おまじない, 引き寄せ |
| @Senba_Kaientai | 225,314 | Financial Analyst | Finance, Organization, Taxation |
| @jetboat26 | 186,326 | Blogger | Tech, Music, Thailand |
| @Fritolay_JP | 174,361 | Snack Manufacturer | Snack, Manufacturer, Campaign |
| @iamriki2010 | 102,646 | Unknown | N/A |
| @kamechan7407 | 93,009 | Mascot | Drums, Mascot, Cats |
| @hidetoshitwitt | 86,080 | Tech Blogger | Gadgets, Soccer, Music |
| @lkQDSNT1BhrOCHd | 78,764 | - | - |
| @AORUS_Brasil | 60,110 | Gaming | Gamer, Premium, Novidades |
| @dospara_repair | 56,572 | PC修理 | PC Repair, Computer Store, Assembly Services |
Top Keywords in Follower Bios
Top Hashtags in Follower Bios
7,237
Followers With Bio
2,763
Followers Without Bio
72.37%
% With Bio
27.63%
% 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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Export tweets with engagement metrics, timestamps, media, and reply/retweet details as CSV.
Buy Tweets - from $15Viral Tweets
Top 5 by likes+RTs from 3,239 analyzed51,741
Combined Engagement
8,568
Total Likes
43,173
Total Retweets
10,348
Avg per Tweet
Key Metrics for Viral Tweets
0%
With Media
0%
With Hashtags
100%
With @Mentions
100%
With Links
Topical Analysis:
RT @livedoornews: 【あとわずか】Internet Explorer、日本時間6月16日でサポート終了 27年の歴史に幕 https://t.co/LqUcyE73y2 Microsoftは2021年5月にIEデスクトップアプリのサポートを終了することを発表。ユーザーに対しMicrosoft Edgeブラウザへの切り替えを促してきた。 https://t.co/X6fDadz94Z
【AORUS 新春ゲーマー支援キャンペーン】 ゲーミングといえば AORUS でしょ！ 【応募方法】 ・@AORUS_JP フォロー ・このツイートを RT ・欲しい景品をリプライしてね 【進呈品】 A賞「G27FC A」1名様 B賞「Z590 AORUS PRO AX」1名様 C賞「AORUS M5」3名様 応募期間: 2022年05月08日まで https://t.co/Iv866IDZqq
【さらばだ2022年！年末万歳！！】 今年もそろそろ終わり... 年末をパーッと締め括りたいですね。 【応募方法】 ・@AORUS_JP フォロー ・このツイートを RT & 何か (来年の抱負等) リプライしてね 【進呈品】 「G27FC A ゲーミング液晶ディスプレイ」を1名様へ 応募期間: 2022年12月18日まで https://t.co/pMb4prBHL6
【週刊ドスパラ TV 特別キャンペーン】 生放送で組み立てた、あのパソコンを差し上げます！ 【応募方法】 ・@AORUS_JP & @dospara_web フォロー ・このツイートを RT & 組立放送の感想をリプライしてね 【進呈品】 ・「村井さんが組み立てた PC」を1名様へ 応募期間: 2023年04月13日まで https://t.co/k3x1vpOm53
RT @pc_watch: 藤井聡太竜王、AMDのブランド広告に出演 https://t.co/HtvboQZcWf https://t.co/MAHYjlI5li
Key Insights & Takeaways
账号通过抽奖活动提高用户参与度和品牌曝光 内容以促销和产品宣传为主，吸引目标用户关注 高互动率表明用户对活动和产品信息有较强兴趣
Strengths
- + Established follower base of 87,834
- + 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 @AORUS_JP reveals an growing Twitter presence with 87,834 followers. The account demonstrates a content-creator strategy, averaging 66.7 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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