AAAI Conference 2016 Conference Paper
EKNOT: Event Knowledge from News and Opinions in Twitter
- Min Li
- Jingjing Wang
- Wenzhu Tong
- Hongkun Yu
- Xiuli Ma
- Yucheng Chen
- Haoyan Cai
- Jiawei Han
We present the EKNOT system that automatically discovers major events from online news articles, connects each event to its discussion in Twitter, and provides a comprehensive summary of the events from both news media and social media’s point of view. EKNOT takes a time period as input and outputs a complete picture of the events within the given time range along with the public opinions. For each event, EKNOT provides multi-dimensional summaries: a) a summary from news for an objective description; b) a summary from tweets containing opinions/sentiments; c) an entity graph which illustrates the major players involved and their correlations; d) the time span of the event; and e) an opinion (sentiment) distribution. Also, if a user is interested in a particular event, he/she can zoom into this event to investigate its aspects (subevents) summarized in the same manner. EKNOT is built on real-time crawled news articles and tweets, allowing users to explore the dynamics of major events with minimal delays.