SocialNLP 2015 - 3rd International Workshop on Natural Language Processing for Social Media (SocialNLP 2015)

With social media services' rise of popularity, including general-purpose Microblogs such as Facebook, Twitter, and Plurk, goal-oriented services such as Linkedln (for professional occupation), Del.icio.us (a social bookmarking service), and Foursquare (a check-in service for mobile devices), and Web 2.0-based large-scale knowledgebase such as Wikipedia and common-sense corpus, now researchers can assess heterogeneous information of the target human/object that includes not only text content but also meta-data, or even the social relationships among persons.
Furthermore, the content on social media and Web 2.0 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. It is not suitable to apply existing natural language techniques on such content because they are not tailored to do so. For instance, standard summarization techniques might not be suitable for Plurk posts that are relatively short and contain responses from multiple friends; and sentiment dictionaries learned from news corpus might not be suitable for sentiment detection tasks on Microblogs.
As it is generally believed social media has become one of the major means for communication and content producing, while such trend is not likely to fade away, being able to process content from social media platforms does bring a lot of values in real-world applications. Furthermore, due to the change of the style to the content and the availability of heterogeneous resources (e.g. social relationship among people) one can obtain, novel NLP techniques that are designed specifically for such platform and can potentially integrate or learn information from different sources are highly demanded. Below we highlight some (non-exclusive) important themes in this direction.
Organizing the SocialNLP workshop in WWW 2015 is three-fold. First, social media data is essentially generated and collected from online social services that are func-tioned based on Web techniques. One can take advantage of the knowledge of Web techniques to investigate various kinds of user behaviors in social media and investigate the interactions between users. Second, user-generated data in social media is mainly in the form of text. Theories and techniques on Web information retrieval and natural lan-guage processing are desired for semantic understanding, accurate search, and efficient processing of big social me-dia data. Third, from the perspective of application, if so-cial media data can be effectively processed to distill the collective knowledge of users, novel Web applications, such as emergency management, social recommendation, and future prediction, can be developed with higher accuracy and better user experience. We expect SocialNLP workshop in WWW community can provide mutually-reinforced benefits for researchers in areas of Web techniques, information retrieval and social media analytics.
On the other hand, we organizing SocialNLP in NAACL 2015 because of the following rationales. First, social media analysis and sentiment analysis are two research topics which are closely related to natu-ral language processing. Moreover, their development highly depends on NLP techniques due to textual data. In recent NAACL/ACL/EMNLP conferences, no matter to tell from the number of submissions or participants, it is apparent that they are certainly two of the biggest research communities. Second, social media data consists of not only social connections but also a plentiful of interaction textual con-tents, such as short messages, comments, and opinions. Processing such big social data with linguistic knowledge and NLP techniques has encountered many important research problems. In short, hosting SocialNLP workshop in NAACL will provide mutually-reinforced benefits for researchers in areas of Web techniques, natural language processing and social media analytics. We believe collecting thoughts and comments of these researchers will also bring up many great ideas and opportunities for future re-search collaborations.
Topics of Interest
Topics of interests for the workshop include, but are not limited to:
Content analysis on Social Media
Concept-level sentiment analysis
Summarization of posts/replies on social media
Name entity Recognition on Social media
Relationship extraction on social media
Entity resolution for social media
Search, Indexing, and Evaluation on Social Web
Improving Speech Recognition using Social Media Content
Multilingual and Language specific Information Retrieval on Social Web
Natural language processing on Web 2.0
Folksonomy and Social Tagging
Trend analysis on Wikipedia
Trustworthiness analysis on Wikipedia
Human computing for social-media corpus generation
Social structure and position analysis using Microblog content
Trust and Privacy analysis in social contexts
Community detection using blogs or Microblog content
Sentiment and Opinion Analysis on Social Media
Big social data analysis
Lexical semantic resources, corpora and annotations of social media for sentiment analysis
Opinion retrieval, extraction, classification, tracking and summarization
Domain specific sentiment analysis and model adaptation Emotion detection
Sentiment analysis for automatic public opinion poll and surveys of user satisfaction
Improvement of NLP tasks using subjectivity and/or sentiment analysis on social platform
Sentiment analysis and human computer interface on social platform
Real-world sentiment applications and systems on social platform
Models and Tools Development for SocialNLP
Biologically-inspired opinion mining
Social-network motivated methods or tools for natural language processing
Advanced topic model for social media
Learning to rank for social media
Clustering and Classification tools for Social Media
Content-based and social-based Recommendation
Multi-lingual machine translation on Microblog