An Evaluation Method for Content Analysis Based on Twitter Content Influence

Euijong Lee, Young Gab Kim, Young Duk Seo, Kwangsoo Seol, Doo Kwon Baik

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Twitter is a microblogging website, which has different characteristics from any other social networking service (SNS) in that it has one-directional relationships between users with short posts of less than 140 characters. These characteristics make Twitter not only a social network but also a news media. In addition, Twitter posts have been used and analyzed in various fields such as marketing, prediction of presidential elections, and requirement analysis. With an increase in Twitter usage, we need a more effective method to analyze Twitter content. In this paper, we propose a method for content analysis based on the influence of Twitter content. For measuring Twitter influence, we use the number of followers of the content author, retweet count, and currency of time. We perform experiments to compare the proposed method, frequency, numerical statistics, user influence, and sentiment score. The results show that the proposed method is slightly better than the other methods. In addition, we discuss Twitter characteristics and a method for an effective analysis of Twitter content.

Original languageEnglish
Pages (from-to)841-867
Number of pages27
JournalInternational Journal of Software Engineering and Knowledge Engineering
Volume27
Issue number5
DOIs
Publication statusPublished - 2017 Jun 1

Keywords

  • content influence
  • follower
  • retweet
  • Twitter

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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