Exploiting social media for Army operations: Syrian crisis use case

Sue E. Kase; Elizabeth K. Bowman; Tanvir Al Amin; Tarek Abdelzaher

doi:10.1117/12.2049701

22 May 2014 Exploiting social media for Army operations: Syrian crisis use case

Sue E. Kase, Elizabeth K. Bowman, Tanvir Al Amin, Tarek Abdelzaher

Proceedings Volume 9122, Next-Generation Analyst II; 91220D (2014) https://doi.org/10.1117/12.2049701
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

Millions of people exchange user-generated information through online social media (SM) services. The prevalence of SM use globally and its growing significance to the evolution of events has attracted the attention of the Army and other agencies charged with protecting national security interests. The information exchanged in SM sites and the networks of people who interact with these online communities can provide value to Army intelligence efforts. SM could facilitate the Military Decision Making Process by providing ongoing assessment of military actions from a local citizen perspective. Despite potential value, there are significant technological barriers to leveraging SM. SM collection and analysis are difficult in the dynamic SM environment and deception is a real concern. This paper introduces a credibility analysis approach and prototype fact-finding technology called the “Apollo Fact-finder” that mitigates the problem of inaccurate or falsified SM data. Apollo groups data into sets (or claims), corroborating specific observations, then iteratively assesses both claim and source credibility resulting in a ranking of claims by likelihood of occurrence. These credibility analysis approaches are discussed in the context of a conflict event, the Syrian civil war, and applied to tweets collected in the aftermath of the Syrian chemical weapons crisis.

Citation Download Citation

Sue E. Kase, Elizabeth K. Bowman, Tanvir Al Amin, and Tarek Abdelzaher "Exploiting social media for Army operations: Syrian crisis use case", Proc. SPIE 9122, Next-Generation Analyst II, 91220D (22 May 2014); https://doi.org/10.1117/12.2049701

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