A values and psychological attribute analysis of the Scottish Independence Referendum context in Twitter

Caroline A. Halcrow, Qingpeng Zhang
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Abstract

Schwartz (Andrew) [1] argues that inter-disciplinary approaches involving computational linguistics and the social sciences are needed to make sense of big data in social networks. The social psychology tool, the Schwartz (Shalom) Values Model [2] is used here alongside linguistic psychological attribute analysis to investigate a context in 'Twitter'. The topic of the Scottish Independence Referendum (September 18th, 2014) was selected as the context because it divided opinion into camps. This study's main hypothesis is that the camps of contexts can be values-profiled. Secondary hypotheses are: the values profiles correlate with psychological attribute profiles in the different voting camps; and the psychological textual analysis adds a wider psychological dimension to topic modeling in 'Twitter'. The methodology combined two processes: the assignment of values to the camps of the Referendum context using the Schwartz Values Model [2]; and the content analysis of the tweets, using the psychological textual analysis tool, LIWC.
推特中苏格兰独立公投语境的价值观与心理属性分析
Schwartz (Andrew)[1]认为,需要使用涉及计算语言学和社会科学的跨学科方法来理解社交网络中的大数据。社会心理学工具Schwartz (Shalom)价值观模型[2]在这里与语言心理属性分析一起使用,以调查“Twitter”中的上下文。选择苏格兰独立公投(2014年9月18日)的主题作为背景,因为它将意见分成了阵营。本研究的主要假设是语境的阵营可以被价值描述。次要假设是:不同投票阵营的价值观特征与心理属性特征相关;心理文本分析为“推特”中的话题建模增加了更广泛的心理维度。该方法结合了两个过程:使用施瓦茨价值观模型[2]将价值观分配给公投背景下的阵营;以及使用心理学文本分析工具LIWC对推文进行内容分析。
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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