Finding prophets in the blogosphere: bloggers who predicted buzzwords before they become popular
Finding prophets in the blogosphere: bloggers who predicted buzzwords before they become popular
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DOI：
10.1145/2837185.2837188
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
Jianwei Zhang;Seiya Tomonaga;Shinsuke Nakajima;Y. Inagaki;Reyn Y. Nakamoto
中科院分区：
文献类型：
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作者：
Jianwei Zhang;Seiya Tomonaga;Shinsuke Nakajima;Y. Inagaki;Reyn Y. Nakamoto
从社交媒体中识别重要用户是信息和知识管理领域的一个重要研究课题。虽然研究者们关注的是用户在社交网络中对某个话题的知识水平或对其他用户的影响程度，但以往的研究并没有研究用户对未来流行度的预测能力。在本文中，我们提出了一种新的方法，根据流行语预测能力来发现重要的博主。我们在博客圈中进行了时间序列分析，考虑了四个因素：帖子提前，内容相似性，条目频率和流行语覆盖率。我们做的准备工作是将一个博主分成知识丰富的类别，识别过去的流行语，分析流行语的高峰期内容和成长期，最后评估博主对流行语和类别的预测能力。实验结果表明，该方法可以找到预言性的博客，并优于其他不考虑时间特征的博客数据。
Identifying important users from social media has recently attracted much attention in information and knowledge management community. Although researchers have focused on users' knowledge levels on certain topics or influence degrees on other users in social networks, previous works have not studied users' prediction ability on future popularity. In this paper, we propose a novel approach to find important bloggers based on their buzzword prediction ability. We conduct a time-series analysis in the blogosphere considering four factors: post earliness, content similarity, entry frequency and buzzword coverage. We perform preparatory work in categorizing a blogger into knowledgeable categories, identifying past buzzwords, analyzing a buzzword's peak time content and growth period, and finally evaluate a blogger's prediction ability on a buzzword and on a category. Experimental results on real-world blog data consisting of 150 million entries from 11 million bloggers demonstrate that the proposed approach can find prophetic bloggers and outperforms others that do not take temporal features into account.