Finding News-Topic Oriented Influential Twitter Users Based on Topic Related Hashtag Community Detection
Finding News-Topic Oriented Influential Twitter Users Based on Topic Related Hashtag Community Detection
复制标题
DOI：
--
复制
发表时间：
2014-11
期刊：
影响因子：
--
通讯作者：
Feng Xiao;T. Noro;T. Tokuda
中科院分区：
文献类型：
--
作者：
Feng Xiao;T. Noro;T. Tokuda
近年来，越来越多的用户愿意在Twitter上收集和提供有关新闻话题的信息，Twitter是最流行的微博客服务之一。由Twitter中的主题标签定义的虚拟社区是为了交换有关新闻主题的信息而创建的。在这些社区中找到与新闻主题相关的有影响力的Twitter用户将有助于我们了解为什么某些观点很受欢迎，并为新闻主题提供有价值和可靠的信息。在本文中，我们提出了一种新的方法来检测新闻主题相关的用户社区定义的主题标签的基础上特征共现词检测。我们还提出了RetweetRank和MentionRank，发现两种类型的有影响力的Twitter用户从这些新闻主题相关的社区用户的转推和提及活动的基础上。实验结果表明，我们的特征共现词检测方法可以检测出与新闻主题高度相关的词。RetweetRank可以找到有影响力的Twitter用户，他们关于新闻主题的推文很有价值，更有可能引起其他人的兴趣。MentionRank可以找到在新闻话题上具有高度权威的有影响力的Twitter用户。我们的方法在评估中也优于其他相关方法。
Recently, more and more users would like to collect and provide information about news topics in Twitter, which is one of the most popular microblogging services. Virtual communities defined by hashtags in Twitter are created for exchanging information about the news topic. Finding influential Twitter users in these communities related to a news topic would help us understand why some opinions are popular, and get valuable and reliable information for the news topic. In this paper, we propose a new approach to detect news-topic-related user communities defined by hashtags based on characteristic co-occurrence word detection. We also propose RetweetRank and MentionRank to find two types of influential Twitter users from these news-topic-related communities based on user's retweet and mention activities. Experimental results show that our characteristic co-occurrence word detection methods could detect words which are highly relevant to the news topic. RetweetRank could find influential Twitter users whose tweets about the news topic are valuable and more likely to interest others. MentionRank could find influential Twitter users who have high authority on the news topic. Our methods also outperform other related methods in evaluations.