Challenges in the use of social media data for the next generation analyst

Abstract

This paper discusses the opportunities and challenges present for the next generation analyst in the use of social media data. Focusing particularly on the detection of deception and misinformation within the latter, a review of current approaches is followed by the elaboration of a theoretical model for social media analysis premised on activity based intelligence. Considering this model with regard to latent challenges to analytical performance and potential opportunities for analytical calibration, this discussion articulates an approach for open-source, next generation intelligence analysis.

Antecedents and outcomes of enterprise social network usage within UK higher education

“…Therefore, reposting reduced worker response time to consumer demands, the decreased time needed for new employee preparation and improved overall customer service (Kankanhalli et al , 2011). Panahi and Ziaeemehr (2015); Grace and Leskovich (2015); and Kywe et al (2012) have argued that tagging increases users’ chances to discover and retrieve new knowledge via the use of tagging.…”

Social Media Systems in the Workplace: Toward Understanding Employee Knowledge Creation via Microblogging within Shared Knowledge Domains

“…Some researchers have argued that tagging increases users' chances to discover and retrieve new knowledge via the use of tagging [79]. With 500 million Twitter posts daily [80], it is unlikely that a user can discover posts that contain needed knowledge within a shared domain without proper content categorization. Topical categorization of posts becomes more essential since studies show that only 40% of all tweets are original (the remainder are repeated by the general Twitter population).…”

Privacy, Trust, and Manipulation in Online Relationships

“…Similarly, we believe that the findings of this paper constitute a major step towards understanding online deception, and provide a solid theoretical background for future work in this regard. In fact, online deception (Grace & Leskovicha, 2015;Lee & Wright, 2016;Tsikerdekis & Zeadally, 2014) represents one of the recent research areas that needs collaborative efforts of psychology, sociology, and computer science. The costs of deception related to social media environments lead to several technical challenges that both developers and users must address.…”