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SMUC-TIST 2010 : ACM TIST Special Issue on Search and Mining User Generated Contents

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Link: http://tist.acm.org/CFPs/TIST-SI-SMUC.pdf
 
When Dec 1, 2010 - Dec 1, 2010
Where ACM TIST
Submission Deadline Dec 1, 2010
Notification Due Feb 1, 2011
Final Version Due Mar 1, 2011
Categories    social media   data mining   information retrieval   artificial intelligence
 

Call For Papers

Deadline: 1 December 2010
More info at ACM TIST webpage

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.
The primary goal of this special issue of ACM Transactions on Intelligent Systems and Technology is to foster research in the interplay between Social Media, Data/Opinion Mining and Search, aiming to reflect the actual developments on technologies that exploit user generated contents.

Topics of Interest

We invite researchers and professionals from a broad range of disciplines to submit to this special issue. Papers may encompass any or all of the following types of works: foundational theoretical analyses, modelling, simulation, and empirical studies. Moreover, authors may examine different aspects of search and mining user generated contents in a variety of possible contexts. Topics of interest include, but are not limited to:


A) Mining Social Media

* Social networks analysis/mining
* Tagging/links/graphs analysis and mining
* Community detection and evolution
* Influence, trust and privacy analysis
* Social media monitoring/analysis

B) Opinion Mining and Sentiment Analysis

* Opinion extraction/classification/summarization/visualization
* Temporal sentiment analysis
* Cross-lingual/cross-domain sentiment analysis
* Irony detection in opinion mining
* Wish analysis
* Product review analysis

C) Search in Social Media

* Novel social search algorithms
* Social ranking
* Multi-entity search
* Multifaceted search
* User Modelling and Personalization in Social Media

D) Other Social Intelligent Systems

* Social Recommender systems
* Semantic Social Media
* Market analysis
* Cross-lingual/cross-domain social intelligent systems

Submission Guidelines

Manuscripts submitted to the special issue should contain original material not published in nor submitted to other journals. Each paper will be reviewed by at least 3 expert reviewers. Papers which do not meet publication quality standards, or does not pass the editorial assessment of suitability of this special issue will be rejected before the review process.
Full papers should be sent via TIST's On-Line Submission system http://mc.manuscriptcentral.com/tist (please select “Special Issue: Search and Mining User Generated Contents” as the manuscript type), and should not exceed 20 pages length. Details of the journal and manuscript preparation are available on the website: http://tist.acm.org/

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