Viral Memetics (VIRAL) A Workshop of the 8th International Joint Conference on Social Informatics (SocInfo-2016) Bellevue, WA, USA | Monday, November 14, 2016
Workshop Overview

VIRAL 2016: Workshop on Viral Memetics

International Conference on Social Informatics

Scope and Focus

This workshop focuses on analyzing and understanding both the quantitative and qualitative spread of derivative ideas. Of particular interest are linguistic memes such as memorable quotations and variants thereof, unique hashtags and phrases, visual memes and their variants, and identifiable elements of viral videos. Another core focus is the tracking and prediction of viral spread, and the identification of derivative works. The target audience includes social scientists specializing in computer-mediated communications, network scientists, computational linguists, and researchers in the psychology of visual and audiovisual media.

Active research areas that are relevant to viral memes include:

The emphasis of this workshop shall be approaches based on analysis of viral content and spread from sources including but not limited to: social media, social news, collaboration networks, and document collections.

Application areas that often exhibit a need for viral memetic analysis include:

Intended Audience and Impact

We welcome paper submissions from researchers in all areas of the study of memes and viral informatics listed in the above section describing the workshop scope. We also hope to attract SocInfo participants from industrial R&D with interesting current applications that showcase aspects of heterogeneity in social and other networks.

This workshop shall help to bring together people from these different areas and present an opportunity for researchers and practitioners to share new techniques for identifying and analyzing relationships in networks that integrate multiple types or sources of information. We also propose to coordinate with research communities in related areas of specialization such as: social influence, trending topics, community detection, and heterogeneous information network analysis to find opportunities for cross-fertilization and interdisciplinary collaboration.

Relevant media include, but are not limited to, forums, blogs, systems such as Twitter, YouTube, Facebook, Pinterest, Tumblr, Snapchat, Google+, LinkedIn, etc. Of particular interest are descriptive metadata, content admitting audiovisual analysis (including deep learning for action or event recognition, sentiment analysis, etc., in images and video), spatiotemporal and network traffic statistics, tracking mechanisms, and forensic (e.g., stylographic) analysis of content modification. However, the scope is not limited to any particular approach to link analysis or any source of viral meme information such as image or text corpora.

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