Graph-Based Multi-Tweet Summarization using Social Signals
Xiaohua Liu, Yitong Li, Furu Wei, Ming Zhou · International Conference on Computational Linguistics · 2012
We study the multi-tweet summarization task, which aims to find representative tweets from a given set of tweets. Multi-tweet summarization allows people to quickly grasp the essential meaning of a large number of tweets. It can also be used as a pre-processing component for information extraction tasks on tweets. The challenge of this task lies in computing a tweet’s salience score with little information in a single tweet. We propose a graph-based multi-tweet summarization system that incorporates social network features, which make up for the information shortage in a tweet. Another distinguished feature of our system is that tweet readability and user diversity are considered. We evaluate our system on a manually annotated dataset, and show that our system outperforms the stateof-the-art baseline. We further evaluate our method in a real scenario of summarization of Twitter search results and demonstrate its effectiveness. Title and Abstract in another language (Chinese)