论文标题
衡量Facebook对研究的反应的多样性
Measuring the Diversity of Facebook Reactions to Research
论文作者
论文摘要
在线和现实世界中,社区围绕核心问题的情感共识融合在一起。对科学发现的情感反应通常在这些核心问题中起关键作用。当对科学主题有太多的看法时,情绪爆发并引起冲突。这种冲突威胁着研究的积极成果。情绪有能力塑造人们如何处理新信息。他们可以使公众对科学的理解,激励政策立场,甚至改变生活。然而,几乎没有做过使用定量方法来评估公众对科学的情感反应的工作。在本文中,我们使用对Facebook上学术文章的响应的数据集来分析情感价,强度和多样性的动态。我们提出了一种基于点击的反应的新颖方法,可以提高其可理解性,并使用这些加权反应来开发总体情绪反应的新指标。我们将指标与LDA主题模型和统计测试一起使用,以调查用户的情感反应与一个科学主题与另一个科学主题的不同。我们发现,与其他研究主题相比,与性别,遗传学或农业/环境科学有关的研究文章与用户的情感反应显着不同。我们还发现,通常对Facebook上的科学研究有积极的反应,并且产生积极情绪反应的文章更有可能被广泛分享 - 这与先前对其他社交媒体平台的研究相矛盾。
Online and in the real world, communities are bonded together by emotional consensus around core issues. Emotional responses to scientific findings often play a pivotal role in these core issues. When there is too much diversity of opinion on topics of science, emotions flare up and give rise to conflict. This conflict threatens positive outcomes for research. Emotions have the power to shape how people process new information. They can color the public's understanding of science, motivate policy positions, even change lives. And yet little work has been done to evaluate the public's emotional response to science using quantitative methods. In this paper, we use a dataset of responses to scholarly articles on Facebook to analyze the dynamics of emotional valence, intensity, and diversity. We present a novel way of weighting click-based reactions that increases their comprehensibility, and use these weighted reactions to develop new metrics of aggregate emotional responses. We use our metrics along with LDA topic models and statistical testing to investigate how users' emotional responses differ from one scientific topic to another. We find that research articles related to gender, genetics, or agricultural/environmental sciences elicit significantly different emotional responses from users than other research topics. We also find that there is generally a positive response to scientific research on Facebook, and that articles generating a positive emotional response are more likely to be widely shared---a conclusion that contradicts previous studies of other social media platforms.