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Semantic Software Lab
Concordia University
Montréal, Canada

EACL 2012 Workshop on Semantic Analysis in Social Networks

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EACL 2012 Workshop on Semantic Analysis in Social Networks
April 23, 2012, Avignon, France

Submission Deadline: Jan 30, 2012


Semantic analysis in social networks (SN) is important for applications such as understanding and enabling social networks, natural language interfaces and human behaviour on the web, e-learning environments, cyber communities and educational or online shared workspaces. These aspects are also important in security, privacy & identity, opinion mining, sentiment analysis, and in the larger area of affective computing.

This workshop will provide a forum for discussion between leading names and researchers involved in text analysis and social networks in the context of natural language understanding, natural language generation, automatic categorization, topic detection, emotion analysis, and applications using computational approaches to process social networks. Besides methodologies and techniques for SN analysis, we also encourage the submission of papers that experiment with and describe applicative contexts in which analysis and detection of affective aspects are useful and beneficial.

Topics of interest include, but are not limited to:

- semantic analysis in sentences and web content from social networks

- classification of texts by emotion and mood from SN

- sociology of emotions and influence on inter-personal communications

- topic detection and clustering in SN

- SN analysis across different languages

- SN analysis from multimedia (text, speech, video)

- security and privacy issues in SNs

- automatic summarization from multiple sources and multiple languages

- analysis of sentiment and opinion in SN

- information extraction and indexing

- applications in which affective aspects are beneficial

- tools and resources for accessing, representing, and managing social network data in natural language processing frameworks (e.g., GATE, UIMA)

- other aspects of the computational treatment of SN and affect.