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Visual analysis of online social media to open up the investigation of stance phenomena
Information Visualization ( IF 1.8 ) Pub Date : 2015-03-26 , DOI: 10.1177/1473871615575079
Kostiantyn Kucher 1 , Teri Schamp-Bjerede 2 , Andreas Kerren 1 , Carita Paradis 2 , Magnus Sahlgren 3
Affiliation  

Online social media are a perfect text source for stance analysis. Stance in human communication is concerned with speaker attitudes, beliefs, feelings and opinions. Expressions of stance are associated with the speakers' view of what they are talking about and what is up for discussion and negotiation in the intersubjective exchange. Taking stance is thus crucial for the social construction of meaning. Increased knowledge of stance can be useful for many application fields such as business intelligence, security analytics, or social media monitoring. In order to process large amounts of text data for stance analyses, linguists need interactive tools to explore the textual sources as well as the processed data based on computational linguistics techniques. Both original texts and derived data are important for refining the analyses iteratively. In this work, we present a visual analytics tool for online social media text data that can be used to open up the investigation of stance phenomena. Our approach complements traditional linguistic analysis techniques and is based on the analysis of utterances associated with two stance categories: sentiment and certainty. Our contributions include (1) the description of a novel web-based solution for analyzing the use and patterns of stance meanings and expressions in human communication over time; and (2) specialized techniques used for visualizing analysis provenance and corpus overview/navigation. We demonstrate our approach by means of text media on a highly controversial scandal with regard to expressions of anger and provide an expert review from linguists who have been using our tool.

中文翻译:

网络社交媒体可视化分析开启立场现象调查

在线社交媒体是立场分析的完美文本来源。人类交流中的立场与说话者的态度、信念、感受和意见有关。立场的表达与说话者对他们正在谈论的内容以及在主体间交流中讨论和谈判的内容的看法有关。因此,采取立场对于意义的社会建构至关重要。增加对立场的了解可用于许多应用领域,例如商业智能、安全分析或社交媒体监控。为了处理大量文本数据以进行立场分析,语言学家需要交互式工具来探索文本来源以及基于计算语言学技术的处理数据。原始文本和派生数据对于迭代改进分析都很重要。在这项工作中,我们提出了一种用于在线社交媒体文本数据的可视化分析工具,可用于开启对立场现象的调查。我们的方法补充了传统的语言分析技术,并基于对与两种立场类别相关的话语的分析:情感和确定性。我们的贡献包括(1)描述了一种新的基于网络的解决方案,用于分析人类交流中立场意义和表达的使用和模式随着时间的推移;(2) 用于可视化分析来源和语料库概览/导航的专业技术。我们通过文本媒体就有关愤怒表达的极具争议的丑闻展示了我们的方法,并提供了来自使用我们工具的语言学家的专家评论。我们为在线社交媒体文本数据提供了一种可视化分析工具,可用于开启对立场现象的调查。我们的方法补充了传统的语言分析技术,并基于对与两种立场类别相关的话语的分析:情感和确定性。我们的贡献包括(1)描述了一种新的基于网络的解决方案,用于分析人类交流中立场意义和表达的使用和模式随着时间的推移;(2) 用于可视化分析来源和语料库概览/导航的专业技术。我们通过文本媒体就有关愤怒表达的极具争议的丑闻展示了我们的方法,并提供了来自使用我们工具的语言学家的专家评论。我们为在线社交媒体文本数据提供了一种可视化分析工具,可用于开启对立场现象的调查。我们的方法补充了传统的语言分析技术,并基于对与两种立场类别相关的话语的分析:情感和确定性。我们的贡献包括(1)描述了一种新的基于网络的解决方案,用于分析人类交流中立场意义和表达的使用和模式随着时间的推移;(2) 用于可视化分析来源和语料库概览/导航的专业技术。我们通过文本媒体就有关愤怒表达的极具争议的丑闻展示了我们的方法,并提供了来自使用我们工具的语言学家的专家评论。
更新日期:2015-03-26
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