从描述语语境表征集体注意--以危机事件公众讨论为例
Characterizing Collective Attention via Descriptor Context: A Case Study of Public Discussions of Crisis Events
摘要：
社交媒体数据集可以快速量化对新兴话题和突发新闻（如危机事件）的集体关注。集体关注度通常是通过聚合计数来衡量的，比如提到名字或标签的帖子数量。但根据自然语言交流的理性主义模型，每个实体的集体显著性不仅表现在它被提及的频率上，而且表现在这些提及所采取的形式上。这是因为自然语言交流是基于演讲者和作者对他们的信息将如何被目标受众解释的期望而进行的（并根据其定制）。我们通过对Facebook和Twitter上突发新闻事件的公众在线讨论进行大规模分析来测试这一想法，重点关注最近的五个危机事件。我们研究了人们如何指代地点，特别关注上下文描述符，如“圣胡安”与“波多黎各圣胡安”。“对自然语言交流的描述主义者的解释预测，当期望命名的实体对读者具有高的优先显着性时，这样的描述符将是不必要的（因此被省略）。我们发现，上下文描述符的使用确实与代理的社会和信息的期望，包括宏观层面的因素，如位置的全球显着性和微观层面的因素，如观众参与。我们还发现，在每个危机事件的生命周期中，描述符上下文的使用持续减少。这些发现提供了关于社交媒体用户如何与受众沟通的证据，并指向更细粒度的集体注意力模型，这些模型可能有助于研究人员和危机应对组织更好地了解公众对正在发生的危机事件的看法。
英文摘要：
Social media datasets make it possible to rapidly quantify collective attention to emerging topics and breaking news, such as crisis events. Collective attention is typically measured by aggregate counts, such as the number of posts that mention a name or hashtag. But according to rationalist models of natural language communication, the collective salience of each entity will be expressed not only in how often it is mentioned, but in the form that those mentions take. This is because natural language communication is premised on (and customized to) the expectations that speakers and writers have about how their messages will be interpreted by the intended audience. We test this idea by conducting a large-scale analysis of public online discussions of breaking news events on Facebook and Twitter, focusing on five recent crisis events. We examine how people refer to locations, focusing specifically on contextual descriptors, such as "San Juan" versus "San Juan, Puerto Rico." Rationalist accounts of natural language communication predict that such descriptors will be unnecessary (and therefore omitted) when the named entity is expected to have high prior salience to the reader. We find that the use of contextual descriptors is indeed associated with proxies for social and informational expectations, including macro-level factors like the location's global salience and micro-level factors like audience engagement. We also find a consistent decrease in descriptor context use over the lifespan of each crisis event. These findings provide evidence about how social media users communicate with their audiences, and point towards more fine-grained models of collective attention that may help researchers and crisis response organizations to better understand public perception of unfolding crisis events.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
