比较中的不文明行为:情境、内容和个人特征如何预测不文明内容的暴露程度

IF 3 2区 社会学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Felix Schmidt, Sebastian Stier, Lukas Otto
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引用次数: 0

摘要

不文明行为,即违反谈话的社会规范,在网络政治交流中显然很普遍。虽然越来越多的文献提供了不同网络场所普遍存在不文明行为的证据,但目前仍不清楚网民在哪里以及在多大程度上会受到不文明行为的影响。本文采用比较的方法来评估不同环境、内容和个人特征下的不文明程度。预注册分析使用了详细的网络浏览历史记录,包括研究参与者看到的 Facebook 公开帖子和推文,并结合了 2021 年德国联邦选举期间收集的调查(N = 739)。使用谷歌的透视应用程序接口(Perspective API)对不文明程度进行预测,并在不同背景(平台和竞选期间)、内容特征和个人层面变量之间进行比较。研究结果表明,不文明行为在 Twitter 上尤为突出,在 Facebook 和 Twitter 上,评论比原始帖子/推文更为普遍。以政治内容和政治人物为特征的内容更不文明,而个人特征则是不太相关的预测因素。用户生成的政治内容最有可能成为个人接触不文明行为的来源,这一发现加深了人们对社交媒体对公共话语影响的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Incivility in Comparison: How Context, Content, and Personal Characteristics Predict Exposure to Uncivil Content
Incivility, that is, the breaking of social norms of conversation, is evidently prevalent in online political communication. While a growing literature provides evidence on the prevalence of incivility in different online venues, it is still unclear where and to what extent Internet users are exposed to incivility. This paper takes a comparative approach to assess the levels of incivility across contexts, content and personal characteristics. The pre-registered analysis uses detailed web browsing histories, including public Facebook posts and tweets seen by study participants, in combination with surveys collected during the German federal election 2021 ( N = 739). The level of incivility is predicted using Google’s Perspective API and compared across contexts (platforms and campaign periods), content features, and individual-level variables. The findings show that incivility is particularly strong on Twitter and more prevalent in comments than original posts/tweets on Facebook and Twitter. Content featuring political content and actors is more uncivil, whereas personal characteristics are less relevant predictors. The finding that user-generated political content is the most likely source of individuals’ exposure to incivility adds to the understanding of social media’s impact on public discourse.
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来源期刊
Social Science Computer Review
Social Science Computer Review 社会科学-计算机:跨学科应用
CiteScore
9.00
自引率
4.90%
发文量
95
审稿时长
>12 weeks
期刊介绍: Unique Scope Social Science Computer Review is an interdisciplinary journal covering social science instructional and research applications of computing, as well as societal impacts of informational technology. Topics included: artificial intelligence, business, computational social science theory, computer-assisted survey research, computer-based qualitative analysis, computer simulation, economic modeling, electronic modeling, electronic publishing, geographic information systems, instrumentation and research tools, public administration, social impacts of computing and telecommunications, software evaluation, world-wide web resources for social scientists. Interdisciplinary Nature Because the Uses and impacts of computing are interdisciplinary, so is Social Science Computer Review. The journal is of direct relevance to scholars and scientists in a wide variety of disciplines. In its pages you''ll find work in the following areas: sociology, anthropology, political science, economics, psychology, computer literacy, computer applications, and methodology.
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