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Identifying Domain Experts in the Blogosphere -- Ranking Blogs Based on Topic Consistency

机译:识别博客圈的域专家 - 基于主题一致性的排名博客

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Current ranking algorithms, such as Page Rank, Technorati authority, and BI-Impact, favor blogs that report on a diversity of topics since those attract a large audience and thus more visitors, links, and comments. On the other side, niche blogs with a very specific topic only attract a small audience and thus have only a small reach. This results in a low ranking from today's blog retrieval systems. We argue that the consistency of a blog, i.e. how focused an author reports on a single topic, is a sign for expert knowledge. To find these blogs is particular important for other domain experts to identify blogs that they would like to follow and stay in active contact. To ease the retrieval of expert blogs, i.e. to separate them from the mass of blogs that report on random topics, we introduce a metric for blogs based on topic consistency. We divide the consistency ranking in four different aspects: (1) intra-post, (2) inter-post, (3) intra-blog, and (4) inter-blog consistency. By evaluating the metric with a test data set of 12,000 crawled blogs, we demonstrate the plausibility of our approach.
机译:目前的排名算法,如页面排名,Technorati权威和双重影响,有利于博客,这些博客提交了各种主题的多样性,因为这些主题以来吸引了大型观众,因此更多的访客,链接和评论。另一方面,具有非常具体的主题的利基博客只吸引小受众,因此只有一个小的距离。这导致从今天的博客检索系统排名较低。我们争辩说,博客的一致性,即如何专注于一个主题的作者报告,是专家知识的标志。要查找这些博客对于其他领域专家来说,旨在识别他们希望遵循并保持积极联系的博客,这是特别重要的。为了缓解专家博客的检索,即将它们与报告随机主题的群众分开,我们根据主题一致性向博客引入度量标准。我们划分了四个不同方面的一致性排名:(1)柱子内,(2)职位基,(3)博客内,(4)博客间融合。通过使用12,000个爬行博客的测试数据集评估度量,我们展示了我们方法的合理性。

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