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Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (8): 107-118    DOI: 10.11925/infotech.2096-3467.2020.0091
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Analyzing & Clustering Enterprise Microblog Users with Supernetwork
Xi Yunjiang1,Du Diedie1,Liao Xiao2(),Zhang Xuehong1
1School of Business Administration, South China University of Technology, Guangzhou 510641, China
2School of Internet Finance and Information Engineering, Guangdong University of Finance,Guangzhou 510521, China
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[Objective] This paper proposes an integrated modeling method to process multi-dimensional user interest data, aiming to examine the spectral clustering method for analyzing user interests. [Methods] First, we retrieved Weibo (Microblog) data of "Three Squirrels" and used supernetwork model to integrate the modeling of contents and user interaction data. Then, we constructed an interactive interest index and grouped the users with spectral clustering algorithm. Finally, we evaluated the clustering results with the Silhouette Coefficient and Davies-Bouldin methods. [Results] We found that the clustering DB value reached 0.57 (k was set at 15), which was evenly distributed. [Limitations] More research is needed to further explore user characteristic data and the impacts of different data dimensions on user interests. [Conclusions] This study proposes maintenance and marketing suggestions for enterprise Weibo profiles, which will help them identify user interests and improve marketing effectiveness.

Key wordsSupernetwork      Enterprise Microblog      User Interests      Spectral Clustering     
Received: 10 February 2020      Published: 14 September 2020
ZTFLH:  G206  
Corresponding Authors: Liao Xiao     E-mail:

Cite this article:

Xi Yunjiang, Du Diedie, Liao Xiao, Zhang Xuehong. Analyzing & Clustering Enterprise Microblog Users with Supernetwork. Data Analysis and Knowledge Discovery, 2020, 4(8): 107-118.

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Topics-Keywords Network (Partial)
Users-Topics Network (Partial)
EMTIS Supernetwork
Process of Spectral Clustering Algorithm Based on EMTIS
话题1 话题2
关键词 权重 关键词 权重
双12 0.824 467 合照 0.629 198
福利 0.559 995 自拍 0.336 896
吃土 0.412 233 大咖秀 0.314 599
剁手党 0.412 233 剪刀手 0.314 599
吃货 0.412 233 双十一 0.314 599
Feature Word Extraction Example
用户ID 特征词
2642129313 抱枕、旅游、零食、写真、网页链接、抽奖、玩偶、果干
1042447931 福利、周末、转发、礼包、坚果手机、回家、焕新季
5026461834 游戏、新品、试吃、云果园、果干、猜中、萌宠
Users and Corresponding Feature Words
排名 核心词 频次 排名 核心词 频次
1 主人 478 6 零食 95
2 转发 220 7 年货 75
3 吃货 162 8 投票 71
4 网页链接 152 9 回家 71
5 坚果 151 10 福利 66
Core Feature Word Statistics (Top10)
排名 用户ID 参与话题数 排名 用户ID 参与话题数
1 2238363480 362 6 5497626858 154
2 2389941761 264 7 2834492565 150
3 1939554543 257 8 2267365535 149
4 5348522194 185 9 1712477690 141
5 5591452414 185 10 5208353983 122
User Participation Topic Statistics (Top10)
Silhouette Coefficient Cluster Evaluation
Davies-Bouldin Cluster Evaluation
类团 人数 粉群名称 主要关键词
1 336 旅游爱好者 零食包、神器、处女座、美照、旅行
2 391 宅男宅女 福利、松鼠君、主页菌、周末
3 788 单身狗与情侣 七夕、单身、基友、头像、公仔
4 412 抽奖热衷群体1 坚果手机、实力派、开奖、新技能、潮礼
5 215 新品关注者 云果园、新品、果干、链接
6 389 周边爱好者 头像、漫画、涂鸦、壁纸、大赛
7 666 年货购买者 年货、大礼包、销售额、网页链接、大礼盒
8 312 抽奖热衷群体2 电影票、游戏、萌杯、零嘴
9 343 女生优惠群体 抱枕、优惠券、聚划算、女王、女生节
10 285 学生群体 焕新季、开学礼、礼包
11 236 有家人群 吃货、全家桶、味觉、妈妈、兑换码
12 731 双十一消费者 双11、天猫、光棍节、购物车、淘口令
13 330 求职人群 交流会、招聘、体验师
14 272 抽奖热衷群体3 U 盘、梦想 、广告片、小米手机
15 284 员工群体 年终奖、红包、创始人、团队、春节
User Category and User Group Characteristics
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