ACM TIST Special Issue on Search and Mining User-generated Contents

Social Media have been able to shift the way information is generated and consumed. At first, information was generated by one person and “consumed” by many people, but nowadays most part of the information available in the Web is generated by users, which has changed the needs in information access and management. Social Networks like Facebook or Twitter manage tens of PB of information, with flows of hundreds of TB per day, and hundreds of billions of relationships

User generated content provides an excellent scenario to apply the metaphor of mining any kind of information. In a social media context, users create a huge amount of data where we can look for valuable nuggets of knowledge by applying diverse search (information retrieval) and mining techniques (data mining, text mining, web mining, opinion mining). In this kind of data, we can find both structured information (ratings, tags, links) and unstructured information (text, audio, video), and we have to learn how to combine existing techniques in order to take advantage of the existing information heterogeneity while extracting useful knowledge.
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More info at ACM TIST webpage

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