The last decade has witnessed the blooming era of social media, where people tend to spend more time and effort on online communication, interaction, content-sharing and collaboration than using traditional means. The collection of information on social media channels thus has become a major source for applied research and real applications in various areas. However, it also poses much challenges, where difficulties lie on the incrementally huge size of real data; and the complexity of data contents, currently mostly textual, being involved on social media.
This special session, entitled Natural Language Processing (NLP) for Social Media, aims at coping with the latter. Generally, the content on social media platforms is different from that on others in terms of style, tone, purpose, etc. For instance, posts on Twitter are limited in size, thus can contain jargons, emoticons, or abbreviations which usually do not follow formal grammar. Hence, it is not suitable to apply existing natural language techniques on such content because they are not tailored to do so. Furthermore, due to the change of the style to the content and the availability of heterogeneous resources (e.g. social relationship among people), novel NLP techniques are highly designed for such platforms.
There are three general areas of this theme. First, one may want to investigate and infer user behaviors when functioning on Web-based socia media systems. Second, user-generated data in social media is mainly in the form of text, which prompts new techniques for semantic understanding, accurate search, and efficient processing of big social media data. Third, data mining and information retrieval techniques are demanded for knowledge discovery on social media enviroment, especially for trend prediction of online communities.
In this special session, we encourage contributions concerned with any topics of NLP for Social Media and their derived applications. We expect this special session can provide mutually-reinforced benefits for researchers in areas of natural language processing, Web techniques, information retrieval and social media analytics.Topics of interests for the workshop include, but are not limited to:
Authors who are interested in the above topics can submit their unpublished work to NLP@SocialMedia
2016 special session via EasyChair: https://easychair.org/conferences/?conf=nlpsocialmedia2016.
A clear indication of the motivation and comparison with prior related work should be presented.
Simultaneous submissions to a journal or another conference with refereed proceedings are not allowed.
Submitted papers should be prepared in LNCS style and should not exceed 12 pages. Each paper is to be submitted electronically as a single PDF file through EasyChair. Please read carefully Springer's instructions on preparing the manuscript.
Note that proofs omitted due to space constraints must be placed in an appendix to be read by the program committee members at their discretion. All accepted papers must be presented by one of the authors who must register for the conference and pay the fee.
The proceedings of CSoNet 2016 will be published by Springer in series Lecture Notes in Computer Science (LNCS) and will be distributed at the conference. Selected papers can be invited to publish in special issues of Journal of Combinatorial Optimization (ISI) and Computational Social Networks (Springer).
August 2-4, 2016 - Ho Chi Minh City, Viet Nam