InfluenceRank: A machine learning approach to measure influence of Twitter users

被引：0

作者：

Nargundkar, Ashish ^{[1
]}

Rao, Y. S. ^{[2
]}

机构：

[1] Sardar Patel Inst Technol, Dept Comp Engn, Bombay, Maharashtra, India

[2] Sardar Patel Inst Technol, Dept Elect & Telecommun Engn, Bombay, Maharashtra, India

来源：

2016 5TH INTERNATIONAL CONFERENCE ON RECENT TRENDS IN INFORMATION TECHNOLOGY (ICRTIT) | 2016年

关键词：

social media influence; Twitter; machine learning; PageRank; support vector regression; influence measurement;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We devise a system for measuring influence of Twitter users, which we call InfluenceRank, based on certain features extracted from their Twitter profiles and tweets authored over the duration of two months. As in the real world, influence of a user on social media may be judged by the engagement they drive through the content they publish. For a tweet, engagement can be most obviously measured by the number of retweets (RTs), favourites and replies it gets. Our system comprises of a regression based machine learning approach with InfluenceRank as the predictor variable against the set of our proposed features. The regression model has shown reasonable accuracy despite being fit on limited data.

引用

页数：6

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