Introduction
Social networks on the Web are growing rapidly and offer a fertile ground for data mining and analysis. So many social networks flourish in an unforeseen manner and social data are evolving from various social streams. Such data embed human interactions and interests and their analysis is valuable for detecting trends, events and phenomena on today’s Web reality. Methodologies and techniques of information retrieval, databases, preference modeling, graph theory, etc. have been leveraged and adapted into the social web dynamic environment but still open questions remain in terms of introducing new methodologies which will facilitate trend detection. SoWeTrend workshop has addressed such issues by providing a forum for researchers and practitioners to discuss the social data analytics relevant topics with emphasis on the critical actors in emerging online social networks.
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Vakali, A., Hacid, H. (2013). Introduction to the Proceedings of the Workshop on Social Web Analytics for Trend Detection (SoWeTrend) 2012. In: Haller, A., Huang, G., Huang, Z., Paik, Hy., Sheng, Q.Z. (eds) Web Information Systems Engineering – WISE 2011 and 2012 Workshops. WISE WISE 2011 2012. Lecture Notes in Computer Science, vol 7652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38333-5_19
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DOI: https://doi.org/10.1007/978-3-642-38333-5_19
Publisher Name: Springer, Berlin, Heidelberg
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