在线集体情绪及其对社区生活的影响
Collective emotions online and their influence on community life
摘要：
电子社区，社会群体在网上互动，最近已成为跨学科研究的对象。与面对面的会议一样，互联网交流不仅包括事实信息，还包括情感信息-参与者对所讨论的主题或其他小组成员的感受。众所周知，情绪在离线通信中以多种方式影响交互伙伴是重要的。互联网交流中的情绪是否会影响他人，并系统地影响电子社区轨迹的数量和质量方面？自动情感分析的发展使得使用从网络收集的文本消息进行大规模情感检测和分析成为可能。目前尚不清楚电子社区中的情绪是否主要来自群体成员的个性，或者是否来自群体内的互动，以及它们是否影响群体活动。我们在从博客，Digg和BBC论坛下载的400万个帖子中观察到大规模的情感现象的集体特征。为了测试社区成员的情绪是否会影响其他人的情绪，帖子被分组为具有相似情绪效价的消息集群。长串的频率比情绪随机发生的频率要高得多。集群长度的分布可以用优先过程来解释，因为连续消息的条件概率随集群长度呈幂律增长。对于BBC论坛的帖子，前十条评论中的绝对平均情绪效价值越大，平均讨论长度越高，并且在讨论期间消息中的平均情绪量下降。我们的研究结果证明，集体的情绪状态可以通过互联网通信和情绪表达是维持一些电子社区的燃料创建和调制。
英文摘要：
E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information - how participants feel about the subject discussed or other group members. Emotions are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. It is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. We show the collective character of affective phenomena on a large scale as observed in 4 million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. Our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
