Storia：基于叙事理论的社交媒体内容总结
Storia: Summarizing Social Media Content based on Narrative Theory using Crowdsourcing
摘要：
来自世界各地的人们使用社交媒体来分享对事件的想法和观点，了解人们通过这些渠道所说的话对研究人员，记者和营销人员越来越感兴趣。然而，虽然自动生成的摘要使人们能够有效地使用大量数据，但它们并不提供观众完全理解事件所需的上下文。叙事结构可以为呈现这些数据的顺序和方式提供模板，以创建围绕叙事元素而不是由事实组成的摘要的故事。在本文中，我们使用叙事理论作为识别社交媒体内容之间联系的框架。为此，我们设计了众包任务，根据常用的叙述模板生成事件摘要。在一项对照研究中，对于某些类型的事件，与没有叙事结构的摘要相比，人们更倾向于使用叙事结构创建的故事，也更有可能向其他人推荐它们。
英文摘要：
People from all over the world use social media to share thoughts and opinions about events, and understanding what people say through these channels has been of increasing interest to researchers, journalists, and marketers alike. However, while automatically generated summaries enable people to consume large amounts of data efficiently, they do not provide the context needed for a viewer to fully understand an event. Narrative structure can provide templates for the order and manner in which this data is presented to create stories that are oriented around narrative elements rather than summaries made up of facts. In this paper, we use narrative theory as a framework for identifying the links between social media content. To do this, we designed crowdsourcing tasks to generate summaries of events based on commonly used narrative templates. In a controlled study, for certain types of events, people were more emotionally engaged with stories created with narrative structure and were also more likely to recommend them to others compared to summaries created without narrative structure.
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。
