社交媒体用户传播仇恨言论的网络行为

IF 1.5 Q2 COMMUNICATION
Tadesse Megersa, Abebaw Minaye Gezie
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引用次数: 0

摘要

网络仇恨言论正在撕裂埃塞俄比亚社会,威胁着民主、人类尊严与和平共处的价值观。本研究认为,了解人们对仇恨帖子的反应有助于打击网络仇恨言论。因此,本研究旨在了解社交媒体用户在应对网络仇恨言论时所扮演的角色。为此,在数据收集期间,我们特意从四个被视为仇恨言论传播热点的 YouTube 新闻频道和四个 Facebook 账户的公共空间中收集了 14 篇基于种族的仇恨言论帖子,每篇帖子都有超过 1,000 条评论。然后,使用 "exportcomment.com "从每个仇恨言论帖子中随机收集 100 条评论,该软件可自动从社交媒体帖子中提取 excel 格式的评论。在提取了总共 1,400 条随机评论后,删除了其中的 460 条,因为它们被认为是不相关和不清晰的,无法进行编码和分析。然后,采用归纳编码法来识别、提炼和命名描述社交媒体用户在对仇恨言论做出反应时所扮演的主要角色的代码和主题。研究结果表明,社交媒体用户在应对仇恨内容时扮演了五种主要角色:钓饵、调节节奏、媾和、提供信息和保护。本文对研究结果进行了讨论,并提出了应对网络仇恨言论的必要建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social media users' online behavior with regard to the circulation of hate speech
Online hate speech is ripping Ethiopian society apart and threatening the values of democracy, human dignity, and peaceful coexistence. The current study argues that understanding people's responses to hateful posts helps combat hate speech online. Therefore, this study aims to comprehend the roles social media users play in responding to online hate speech. To this end, 14 ethnic-based hate speech posts each with more than 1,000 comments were collected from the public space of four purposefully selected YouTube news channels and four Facebook accounts, which are considered as hot spots for the circulation of hate speech during data collection period. Then, 100 random comments were collected from each hate speech post using “exportcomment.com” which automatically extract comments from social media posts in excel format. After extracting a total of 1,400 random comments, 460 of them were removed because they were found irrelevant and unclear to be coded and analyzed. Then, inductive coding was employed to identify, refine, and name codes and themes that describe the main roles played by social media users in reacting to the hate speeches. The findings showed five major roles social media users play in responding to hatful contents: trolling, pace-making, peace-making, informing, and guarding. The paper discusses the findings and provides recommendations deemed necessary to counter online hate speeches.
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来源期刊
CiteScore
3.30
自引率
8.30%
发文量
284
审稿时长
14 weeks
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