Anwar Sawood, Giglietto Fabio
Department of Communication and Humanities, University of Urbino Carlo Bo, Urbino, Italy.
Front Sociol. 2024 May 15;9:1379265. doi: 10.3389/fsoc.2024.1379265. eCollection 2024.
In February 2016, Facebook expanded the original "Like" button by introducing five additional "Reactions"-Love, Haha, Wow, Sad, and Angry-using modified versions of Unicode emojis. These reactions enable users to express more nuanced emotions towards posts. This literature review investigates scholarly research on user behavior in response to these reactions, with a focus on a broad spectrum of socioeconomic and psychological issues. We conducted a systematic search across databases including Scopus and Google Scholar, using keywords such as "Facebook" and "Reaction," combined with various key phrases and Boolean operators. Our review synthesizes sixty-four articles published from 2016 to 2023, exploring diverse topics such as political news, far-right and extremist parties, racism, and hate speech during the COVID-19 pandemic. We organized these articles by theme and publication date. Our meta-analysis reveals that lifestyle and entertainment posts predominantly receive positive reactions, while sociopolitical content tends to elicit a broader spectrum of emotions, including negative sentiments. Furthermore, emotionally charged content consistently attracts higher volumes of reactions, regardless of sentiment. This research highlights the intricate relationship between user reactions and content characteristics, providing deeper insights into the dynamics of online engagement. By understanding these interaction patterns, we gain a better grasp of emotional responses and engagement levels, which ultimately shape online discourse and user interactions.
2016年2月,脸书扩展了最初的“点赞”按钮,引入了另外五个“表情反应”——“爱”“哈哈”“哇哦”“悲伤”和“愤怒”,使用的是经过修改的Unicode表情符号版本。这些表情反应让用户能够对帖子表达更细微的情感。这篇文献综述调查了关于用户对这些表情反应的行为的学术研究,重点关注广泛的社会经济和心理问题。我们在包括Scopus和谷歌学术在内的数据库中进行了系统搜索,使用了“脸书”和“表情反应”等关键词,并结合各种关键短语和布尔运算符。我们的综述综合了2016年至2023年发表的64篇文章,探讨了各种主题,如政治新闻、极右翼和极端主义政党、种族主义以及新冠疫情期间的仇恨言论。我们按主题和发表日期对这些文章进行了整理。我们的荟萃分析表明,生活方式和娱乐类帖子主要获得积极的表情反应,而社会政治内容往往会引发更广泛的情感,包括负面情绪。此外,无论情感倾向如何,充满情感的内容始终会吸引更多的表情反应。这项研究突出了用户表情反应与内容特征之间的复杂关系,为在线参与的动态过程提供了更深入的见解。通过了解这些互动模式,我们能更好地掌握情感反应和参与程度,而这最终会塑造在线话语和用户互动。