Twitter in academic events: A study of temporal usage, communication, sentimental and topical patterns in 16 Computer Science conferences

被引:29
作者
Parra, Denis [1 ]
Trattner, Christoph [2 ,3 ]
Gomez, Diego [4 ]
Hurtado, Matias [1 ]
Wen, Xidao [5 ]
Lin, Yu-Ru [5 ]
机构
[1] Pontificia Univ Catolica Chile, Dept Ciencia Computac, Santiago, Chile
[2] Norwegian Univ Sci & Technol, Dept Comp & Informat Sci, Oslo, Norway
[3] Know Ctr, Graz, Austria
[4] Pontificia Univ Catolica Chile, Sch Commun, Santiago, Chile
[5] Univ Pittsburgh, Sch Informat Sci, Pittsburgh, PA 15260 USA
关键词
Twitter; Academic conferences; Evolution over time; Topic models; Sentiment analysis;
D O I
10.1016/j.comcom.2015.07.001
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Twitter is often referred to as a backchannel for conferences. While the main conference takes place in a physical setting, on-site and off-site attendees socialize, introduce new ideas or broadcast information by microblogging on Twitter. In this paper we analyze scholars' Twitter usage in 16 Computer Science conferences over a timespan of five years. Our primary finding is that over the years there are differences with respect to the uses of Twitter, with an increase of informational activity (retweets and URLs), and a decrease of conversational usage (replies and mentions), which also impacts the network structure meaning the amount of connected components of the informational and conversational networks. We also applied topic modeling over the tweets' content and found that when clustering conferences according to their topics the resulting dendrogram clearly reveals the similarities and differences of the actual research interests of those events. Furthermore, we also analyzed the sentiment of tweets and found persistent differences among conferences. It also shows that some communities consistently express messages with higher levels of emotions while others do it in a more neutral manner. Finally, we investigated some features that can help predict future user participation in the online Twitter conference activity. By casting the problem as a classification task, we created a model that identifies factors that contribute to the continuing user participation. Our results have implications for research communities to implement strategies for continuous and active participation among members. Moreover, our work reveals the potential for the use of information shared on Twitter in order to facilitate communication and cooperation among research communities, by providing visibility to new resources or researchers from relevant but often little known research communities. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:301 / 314
页数:14
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