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

机译:Twitter在学术活动中的应用:在16个计算机科学会议上对时间使用,交流,情感和主题模式的研究

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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.
机译:Twitter通常被称为会议的反向渠道。当主要会议在实体环境中举行时,现场和场外参与者通过Twitter上的微博进行社交,介绍新想法或广播信息。在本文中,我们在五年的时间里分析了16次计算机科学会议上学者对Twitter的使用情况。我们的主要发现是,多年来,Twitter的使用存在差异,信息活动(转发和URL)增加,对话使用(回复和提及)减少,这也影响了网络结构的含义。信息和对话网络的连接组件的数量。我们还在推文的内容上应用了主题建模,发现当根据会议的主题对会议进行聚类时,生成的树状图清楚地揭示了这些事件的实际研究兴趣的异同。此外,我们还分析了推文的情绪,发现会议之间存在持续的差异。它还表明,某些社区始终以较高的情感水平来表达信息,而其他社区则以更为中立的方式传达信息。最后,我们研究了一些功能,这些功能可以帮助预测未来用户在在线Twitter会议活动中的参与度。通过将问题归类为分类任务,我们创建了一个模型,该模型可以识别有助于用户持续参与的因素。我们的结果对研究社区实施成员之间持续和积极参与的策略具有重要意义。此外,我们的工作揭示了通过使用Twitter上共享的信息来促进研究社区之间的交流与合作的潜力,方法是通过提供相关但通常鲜为人知的研究社区的新资源或研究人员的可见性。 (C)2015 Elsevier B.V.保留所有权利。

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