Cognos: crowdsourcing search for topic experts in microblogs
Cognos: crowdsourcing search for topic experts in microblogs
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DOI：
10.1145/2348283.2348361
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发表时间：
2012-08
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影响因子：
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通讯作者：
Saptarshi Ghosh;N. Sharma;Fabrício Benevenuto;Niloy Ganguly;K. Gummadi
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作者：
Saptarshi Ghosh;N. Sharma;Fabrício Benevenuto;Niloy Ganguly;K. Gummadi
在拥有数百万用户的微博网站（如Twitter）上寻找话题专家是一个困难而具有挑战性的问题。在本文中，我们提出并研究了一种在流行的Twitter社交网络中发现主题专家的新方法。我们的方法依赖于Twitter人群的智慧——它利用Twitter列表，这些列表通常是由个人用户精心策划的，其中包括他们感兴趣的主题的专家，其元数据（列表名称和描述）为专家的专业领域提供了有价值的语义线索。我们挖掘List信息来构建Cognos，这是一个在Twitter中查找主题专家的系统。基于实际部署的详细实验评估表明：(a) Cognos推断用户的专业知识更准确和全面比最先进的系统,依赖于用户的生物或微博内容,(b) Cognos尺度以及由于内置机制来有效地更新其专家数据库和新用户和(c)尽管仅依赖一个特性,即众包列表,Cognos收益率与结果,如果不是比,那些专家搜索引擎给出的官方Twitter用户测试的范围广泛的查询。我们的研究强调了列表作为Twitter未来内容或专家搜索系统的潜在有价值的信息来源。
Finding topic experts on microblogging sites with millions of users, such as Twitter, is a hard and challenging problem. In this paper, we propose and investigate a new methodology for discovering topic experts in the popular Twitter social network. Our methodology relies on the wisdom of the Twitter crowds -- it leverages Twitter Lists, which are often carefully curated by individual users to include experts on topics that interest them and whose meta-data (List names and descriptions) provides valuable semantic cues to the experts' domain of expertise. We mined List information to build Cognos, a system for finding topic experts in Twitter. Detailed experimental evaluation based on a real-world deployment shows that: (a) Cognos infers a user's expertise more accurately and comprehensively than state-of-the-art systems that rely on the user's bio or tweet content, (b) Cognos scales well due to built-in mechanisms to efficiently update its experts' database with new users, and (c) Despite relying only on a single feature, namely crowdsourced Lists, Cognos yields results comparable to, if not better than, those given by the official Twitter experts search engine for a wide range of queries in user tests. Our study highlights Lists as a potentially valuable source of information for future content or expert search systems in Twitter.