Rumor analysis framework in social media

When a disaster occurred, people try to acquire information through social media such as electronic bulletin boards, SNSs, and video services. Their decision-making tend to be affected by social media information. Sometimes, social media information is useful, so people can get valuable knowledge. On the other hand, social media information is occasionally unreliable. Harmful rumors spread and cause people to panic. In today's information oriented society, a mechanism to detect rumor information in social media has become very important. This paper proposes a framework to detect the rumor information in social media. Our proposed framework clarifies topics in social media, visualizes topic structures in time series variation. Then it extracts rumor candidates and seeks related information from other media such as TV program, newspapers and so on in order to confirm the reliability of rumor candidates. By our framework, potential rumors will be shown.

[1]  Houfeng Wang,et al.  Bootstrapping both Product Properties and Opinion Words from Chinese Reviews with Cross-Training , 2007 .

[2]  Horst Bunke,et al.  On a relation between graph edit distance and maximum common subgraph , 1997, Pattern Recognit. Lett..

[3]  Yukari Shirota,et al.  Graph-based Consumer Behavior Analysis from Buzz Marketing Sites , 2011, EJC.

[4]  Yurie Iino,et al.  Time Series Analysis of R&D Team Using Patent Information , 2009, KES.

[5]  Guangwei Wang,et al.  A Graphic Reputation Analysis System for Mining Japanese Weblog Based on both Unstructured and Structured Information , 2008, 22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008).

[6]  Takahiro Kawamura,et al.  Ontology-Based Topic Extraction Service from Weblogs , 2008, 2008 IEEE International Conference on Semantic Computing.

[7]  W. Scott Spangler,et al.  Intelligent Web Services Selection based on AHP and Wiki , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).