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Submission deadline: March 24, 2015
From a business and government point of view there is an increasing need to interpret and act upon information from large-volume media, such as Twitter, Facebook and Web news. However, knowledge gathered from online sources and social media comes with a major caveat - it cannot always be trusted, nor is it always factual and of high quality. Rumors tend to spread rapidly through social networks, especially in circumstances where their veracity is hard to establish. Researchers have found that people read and rely on untrusted sources for various reasons, the main ones being their interestingness, entertainment value, a friend's online recommendation, or a search engine result. A 2012 report from Pew Internet Research on the future of big data argues that even though by 2020 big data is likely to have a transformational effect on our knowledge and understanding of the world, there is also high risk of "distribution of harms" due to the abundance of inaccurate and false information.
This special issue will focus on the problem of modelling and assessing the trust and veracity of content and information posted in social media, including but not limited to automatic detection, tracking, and visualization of deceptive content, rumors and malicious campaigns, and their spread across media, languages and social networks. The aim of this multidisciplinary special issue is to bring together researchers from Information Retrieval, Web Science, Data Mining, Social Network Analysis, Social Computing, Information Visualization, Natural Language Processing, Multimedia and Human-Computer Interaction, and to combine perspectives and research from Computer Science and Sociology.
While all high-quality manuscripts focused on trust and veracity of information will be considered, we are particularly interested in approaches, applications and case studies with a focus on social media, including online social networks (Twitter, Facebook, Google+, LinkedIn), media sharing applications (Flickr, Instagram, YouTube, DailyMotion, Vine, Imgur), social news (Reddit, Fark, Slashdot), blogging (Tumblr, Blogger), question-answering and knowledge exchange applications (Quora, StackExchange), location-based social networks (Foursquare), reviewing sites (epinions, yelp, TripAdvisor), collaborative authoring environments (Wikipedia), social bookmarking and tagging (Pinterest, StumbleUpon, delicious), and other applications and platforms extensively based on user-generated content and feedback (referred to simply as "social media" below for brevity). Topics of interest include, but are not limited to, the following:
All accepted manuscripts are expected to make a significant scientific contribution and present a rigorous evaluation of the methods they present (e.g., a comprehensive user study should accompany any new visualization proposal).
For submission instructions and reviewing procedure, please refer to http://tois.acm.org/authors.html and add a comment in the email to the Assistant to the Editor-In-Chief that the submission is intended for the special issue on Trust and Veracity of Information in Social Media. All papers will be reviewed by three external reviewers plus at least one guest editor.