iStory: Intelligent Storytelling with Social Data

WWW '20: The Web Conference 2020 Taipei Taiwan April, 2020(2020)

引用 33|浏览25
暂无评分
摘要
The production of knowledge from ever increasing amount of social data is seen by many organizations as an increasingly important capability that can complement the traditional analytics sources. Examples include extracting knowledge and deriving insights from social data to improve government services, predict intelligence activities, personalize the advertisements in elections and improve national security and public health. Understanding social data can be challenging as the analysis goal can be subjective. In this context, storytelling is considered as an appropriate metaphor as it facilitates understanding and surfacing insights which is embedded within the data. In this paper, we focus on the research problem of ‘understanding the social data’ in general and more particularly the curation, summarization and presentation of large amounts of social data. The goal is to enable intelligent narrative construction based on the important features (extracted and ranked automatically) and enable storytelling at multiple levels and from different views using novel summarization techniques. We implement an interactive storytelling dashboard, namely iStory, and focus on a motivating scenario for analyzing Urban Social Issues from Twitter as it relates to the Australian Government Budget, to highlight how storytelling can significantly facilitate understanding social data.
更多
查看译文
关键词
Storytelling, Data Curation, Knowledge Lake, Data Lake, Summarization
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要