...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Information Science >Predicting event mentions based on a semantic analysis of microblogs for inter-region relationships
【24h】

Predicting event mentions based on a semantic analysis of microblogs for inter-region relationships

机译：基于区域间关系的微博语义分析预测事件提及

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

An ability to predict people's interests in different regions would be valuable to many applications including marketing and policymaking. We posit that social media plays an important role in capturing collective user interests in different regions and their dynamics over time and across regions. Event mentions in microblogs of social media like Twitter not only reflect the people's interests in different regions but also affect the posting of future messages as the content of microblogs propagates to others through an online social network. Differentiating from the various network analysis techniques that have been developed to capture people's interests and their propagation patterns, we propose an event mention prediction method that utilises an analysis of inter-region relationships. We first obtain regional user interests for each topic by applying Latent Dirichlet Allocation (LDA) to region-specific collections of tweets and then compute pairwise similarities among regions. The resulting similarity-based region network becomes the basis for constructing region groups through Markov Cluster Algorithm, which helps removing noise relationships among regions. We then propose a relatively simple regression technique to predict future event mentions in different regions. We demonstrate that the proposed method outperforms the state-of-the-art event prediction method, confirming that the novel method of constructing groups from region-based sub-topic interests indeed contributes to the increase in the prediction accuracy.
机译：预测人们在不同地区的兴趣的能力对于包括营销和政策制定在内的许多应用都是有价值的。我们假设社交媒体在捕获不同地区的集体用户兴趣及其随时间推移以及跨地区的动态方面起着重要作用。诸如Twitter之类的社交媒体微博中的事件提及不仅反映了人们在不同地区的兴趣，而且随着微博内容通过在线社交网络传播给其他人，也影响了未来消息的发布。与已经开发来捕获人们的兴趣及其传播方式的各种网络分析技术不同，我们提出了一种利用区域间关系分析的事件提及预测方法。我们首先通过将潜在Dirichlet分配（LDA）应用于特定于地区的推文集合来获得每个主题的地区用户兴趣，然后计算地区之间的成对相似度。由此产生的基于相似度的区域网络成为通过马尔可夫聚类算法构造区域组的基础，这有助于消除区域之间的噪声关系。然后，我们提出了一种相对简单的回归技术来预测不同地区未来发生的事件。我们证明了所提出的方法优于最新的事件预测方法，从而证实了从基于区域的子主题兴趣构建群体的新方法的确有助于提高预测准确性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号