Real-time Social Media Analytics through Semantic Annotation and Linked Open Data

D. Maynard, M. Greenwood, Ian Roberts, George Windsor, Kalina Bontcheva
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引用次数: 7

Abstract

This paper describes an open source framework for analysing large volume social media content, which comprises semantic annotation, Linked Open Data, semantic search, dynamic result aggregation, and information visualisation. In particular, exploratory search and sense-making are supported through information visualisation interfaces, such as co-occurrence matrices, term clouds, treemaps, and choropleths. There is also an interactive semantic search interface (Prospector), where users can save, refine, and analyse the results of semantic search queries over time. These functionalities are presented in more detail in the context of analysing tweets from UK politicians and party candidates in the run up to the 2015 UK general election.
通过语义注释和关联开放数据进行实时社会媒体分析
本文描述了一个用于分析大量社交媒体内容的开源框架,它包括语义注释、链接开放数据、语义搜索、动态结果聚合和信息可视化。特别地,探索性搜索和意义构建通过信息可视化接口得到支持,例如共现矩阵、术语云、树图和脉体。还有一个交互式语义搜索界面(Prospector),用户可以在其中保存、改进和分析语义搜索查询的结果。在分析2015年英国大选前英国政治家和政党候选人的推文的背景下,这些功能将得到更详细的展示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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