社交媒体中的立场——美国总统候选人在脸书和推特上的评论分析

IF 0.1 4区 文学 Q3 HISTORY
Verbum Pub Date : 2018-12-20 DOI:10.15388/VERB.2018.3
R. Kriaučiūnienė, Jefferey La Roux, Miglė Lauciūtė
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引用次数: 0

摘要

【全文及英文摘要】论文的主题是分析网络环境下的立场表达,主要是脸书和推特等社交网络用户对2016年美国总统大选总统候选人的评论。实证数据分析遵循了J.W.Du Bois(2007)、D.Barton&C.Lee(2013)和R.Englebretson(2007)关于立场采取的思想,以及J.W.Du Boies(2007)的立场三角模型,即将立场采取的实例分组为其中一组:评价、影响或认识性,这是本研究的主要框架。语言学家D.Barton和C.Lee(2013)关于在网络环境中表达立场的工作也被考虑在内。考虑到立场识别是一项具有挑战性的任务,即它既可以隐含地表达,也可以明确地表达,并且应该从不同的表达模式中推断出来,并参照许多上下文和互文因素进行解释,在目前的分析中,作者重点解释了社交网络用户在2016年美国总统选举主题的写作空间中使用的语言以及其他多模式的立场表达方式。还应该提到的是,本文中的分析仅提供了对数据的多种可能解释中的一种。此外,本文主要集中于情感立场表达的实证数据的呈现。然而,应该指出的是,在某些情况下,立场类型重叠,即一个例子可以被视为采取情感立场和评价立场,因为判断和评价(即评价立场)通常基于感觉(即情感立场)。实证数据的主要来源是唐纳德·特朗普和希拉里·克林顿在2016年总统竞选期间在经过验证的脸书和推特页面上发表的评论中的立场。总共收集了147个来自社交网络脸书和推特的帖子和评论示例:72条评论包含对唐纳德·特朗普帖子的立场,75条评论包括对希拉里·克林顿帖子的立场。实证数据分析的结果表明,情感立场是通过语言和多模态手段表达的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stance Taking in Social Media: the Analysis of the Comments About Us Presidential Candidates on Facebook and Twitter
[full article and abstract in English] The subject of the paper is the analysis of the expression of stance taking in an online environment, mainly in the comments of users of social networks such as Facebook and Twitter about the presidential candidates of the American Presidential Election in 2016. The empirical data analysis was carried out following the ideas of J. W. Du Bois (2007), D. Barton & C. Lee (2013) and R. Englebretson (2007) on stance taking and J. W. Du Bois’ (2007) model of stance triangle, i.e. grouping instances of stance-taking into one of these groups: evaluation, affect or epistemicity, which served as the main framework of this study. The work of linguists D. Barton & C. Lee (2013) on the expression of stance-taking in an online environment were also taken into consideration. Having in mind the fact that stance identification is a challenging task , i.e. it could be implicitly as well as explicitly expressed and that it should be inferred from different modes of its expression and interpreted with reference to many contextual and intertextual factors, in the current analysis the authors focused on interpretation of linguistic as well as other multimodal means of the expression of stance that were used by users of social networks in their writing spaces on the topic of the Presidential Election in the United States in 2016. It should also be mentioned that the analysis presented in this article offers only one of the many possible interpretations of the data. Moreover, the current paper concentrates mainly on the presentation of the empirical data of the expression of affective stance. However, it should be indicated that in some cases stance types overlap, i.e. one instance could be treated as both taking an affective and an evaluative stance, as judgements and evaluation (i.e. evaluative stance) are often based on feelings (i.e. affective stance). The main source of the empirical data were the instances of stance taking taken from comments found on Donald Trump’s and Hillary Clinton’s verified Facebook and Twitter pages during their presidential campaigns in 2016. All in all, 147 examples of posts and comments from the social networks Facebook and Twitter were collected: 72 comments incorporating stance taking on Donald Trump‘s posts, and 75 comments including stance taking on Hillary Clinton‘s posts. The results of the empirical data analysis showed that the affective stance was expressed by linguistic as well as multimodal means.
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Verbum
Verbum Multiple-
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