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Fusing social network data with hard data
Conference

Fusing social network data with hard data

Abstract

Social networking sites such as Twitter, Facebook and Flickr play an important role in disseminating breaking news about natural disasters, terrorist attacks and other events. They serve as sources of first-hand information to deliver instantaneous news to the masses since millions of users visit these sites to post and read news items regularly. Hence, by exploring efficient mathematical techniques like Dempster- Shafer theory and Modified Dempster's rule of combination, we can process large amounts of data from these sites to extract useful information in a timely manner. In surveillance related applications, the objective of processing voluminous social network data is to predict events like revolutions and terrorist attacks before they unfold. By fusing the soft and often unreliable data from these sites with hard and more reliable data from sensors like radar and the Automatic Identification System (AIS), we can improve our event prediction capability. In this paper, we present a class of algorithms to fuse hard sensor data with soft social network data (tweets) in an effective manner. Preliminary results using real AIS data are also presented.

Authors

Abirami T; Taghavi E; Tharmarasa R; Kirubarajan T; Boury-Brisset AC

Pagination

pp. 652-658

Publication Date

September 14, 2015

Conference proceedings

2015 18th International Conference on Information Fusion Fusion 2015

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