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Sociotechnical Behavior Mining: From Data to Decisions?

Papers from the 2015 AAAI Spring Symposium

Nitin Agarwal, Huan Liu, Laurie Fenstermacher, Program Chair

Technical Report SS-15-05
Published by The AAAI Press, Palo Alto, California.
50 pp., $25.00

Electronic Version of the Technical Report (Download only): $10.00 (Special Introductory Price)

Softcover version of the technical report: $25.00 softcover
(For international orders please shipping options before ordering on website.)
ISBN 978-1-57735-709-4

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Information is extremely critical for efficient decision-making, whether it is for business processes, policy design, or complex military operations confronting a broad spectrum of conflict and human security. However, more information does not always imply more effectiveness. With the advances in ICTs, especially the participatory media (or, social media), information analysts find themselves inundated with data, or rather the "big data". To put things in perspective, a conservative estimate suggests that 2.5 billion gigabytes of data was created every day in 2012, of which 68% was the user generated content or data from social media sites, with no signs of slowing down, in fact doubling up every month. The prevalence of the social media and smart handheld devices has irreversibly transformed our communication, interaction, and information sharing styles, giving rise to novel socio-technical behaviors (for example, "hacktivism", crowdsourcing, self-organization, flash mobs, citizen journalism, "live-tweeting" or "tweetcasting", etc.). Efficient data analysis techniques are needed to understand and model emerging socio-technical behaviors.

Existing studies provide limited understanding of these behaviors. A fundamental and systematic investigation of social media platforms is a precursor to conduct studies at a more foundational level filling this critical research gap. Through this symposium, we intend to create a collaborative and interdisciplinary platform bringing researchers and practitioners from various disciplinary backgrounds, including (but not limited to), computational and information science, social science, cognitive science, mathematics, statistics, economics, among others to share, exchange, learn, and develop preliminary models, new concepts, ideas, principles, and methodologies, aiming to advance the understanding and the current state of research in the socio-technical behavior mining. The outcome of the symposium would serve as a collection of resources that can be used by researchers contributing to a continuous and synergistic advancement of the various disciplines.

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