热门话题社区的检测：桥接内容创建者和分发者
Detection of Trending Topic Communities: Bridging Content Creators and Distributors
摘要：
Twitter或Facebook上的热门话题的兴起导致了一组当前对该话题感兴趣的用户的暂时出现。考虑到这些用户之间的链接的临时性质，能够动态地识别与该热门话题相关的用户社区将允许信息的快速传播。事实上，社区内的个人用户可能会收到其他用户生成的内容推荐，或者社区作为一个整体可以收到与该热门话题相关的新内容的组推荐。在本文中，我们通过识别连贯的主题相关用户组来应对这一挑战，将生成内容的人（创建者）和传播这些内容的人联系起来，例如，通过转发/重新发布（分销商）。这是一个新的问题，在推荐系统的背景下，组到组的互动。对真实Twitter数据的分析将我们的建议与考虑转发活动的基线方法进行比较，并使用标准指标对其进行验证。结果表明，我们的方法可以有效地识别对某个主题感兴趣的社区，每个社区都包括内容创建者和内容分发者，从而促进用户的互动和新信息的传播。
英文摘要：
The rise of a trending topic on Twitter or Facebook leads to the temporal emergence of a set of users currently interested in that topic. Given the temporary nature of the links between these users, being able to dynamically identify communities of users related to this trending topic would allow for a rapid spread of information. Indeed, individual users inside a community might receive recommendations of content generated by the other users, or the community as a whole could receive group recommendations, with new content related to that trending topic. In this paper, we tackle this challenge, by identifying coherent topic-dependent user groups, linking those who generate the content (creators) and those who spread this content, e.g., by retweeting/reposting it (distributors). This is a novel problem on group-to-group interactions in the context of recommender systems. Analysis on real-world Twitter data compare our proposal with a baseline approach that considers the retweeting activity, and validate it with standard metrics. Results show the effectiveness of our approach to identify communities interested in a topic where each includes content creators and content distributors, facilitating users' interactions and the spread of new information.
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。
