The 4th International Workshop on
Natural Language Processing for Social Media
In conjunction with IJCAI 2016 @ July 11, 2016, New York City, USA.
In conjunction with EMNLP 2016 @ November 1, 2016, Austin, TX, USA.


  • The tentative program for SocialNLP@EMNLP 2016 is updateed. Please refer to Program@EMNLP for more details. (2016.10.02)
  • The submission deadline of SocialNLP@EMNLP 2016 was extended to August 12 (23:59 Hawaii Standard Time). (2016.08.04)
  • The workshop date for SocialNLP@EMNLP 2016 is changed to November 1 because the conference dates are shifted to November 1 to 5. (2016.07.30)
  • The program for SocialNLP@IJCAI 2016 is updateed. Please refer to Program@IJCAI for more details. (2016.07.08)
  • The program for SocialNLP@IJCAI 2016 is announced. Please refer to Program@IJCAI for more details. (2016.06.07)
  • The keynote speaker for SocialNLP@IJCAI 2016 is Prof. Yuheng Hu from University of Illinois at Chicago. Please refer to Program@IJCAI for more details. (2016.05.13)
  • The keynote speaker for SocialNLP@EMNLP 2016 is Prof. Cristian Danescu-Niculescu-Mizil from Cornell University. Please refer to Program@EMNLP for more details. (2016.05.13)
  • The submission deadline of SocialNLP@IJCAI 2016 was extended to April 18 (23:59 Hawaii Standard Time). (2016.04.11)
  • The submission site of SocialNLP@EMNLP 2016 was provided. (2016.02.22)
  • The submission site of SocialNLP@IJCAI 2016 was provided. (2016.02.16)
  • SocialNLP 2016 webpage is online. (2015.12.03)

Workshop Description

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), (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 IJCAI 2016 and EMNLP 2016 is four-fold. First, social media analytics is the research topic which is closely related to natural language processing. But with the challenges mentioned above, we resort to the AI community and attempt to find the role of AI and NLP techniques in SocialNLP. In recent NLP-related conferences, no matter to tell from the number of submissions or participants, it is apparent that sentiment analysis and the social media analytics are certainly two of the main research topics. Second, we have a strong program committee (around 100 researchers) this year, in which 88% members have been reviewers for ACL series of conferences, which are top ones for NLP related research, and they can be very helpful in promoting our workshop. Therefore, we believe that the SocialNLP workshop can draw much interest and attract many audiences from potential academic or industrial participants of NLP. We think such high visibility of SocialNLP can bring more participants and submissions to both IJCAI and EMNLP. Third, social media data is essentially generated and collected from online social services, which have accumulated a large number of user-generated social data, i.e., big social data. Processing such big social data with linguistic knowledge and NLP techniques has encountered many important research problems. Through SocialNLP, the cutting edge technology will be introduced to AI researchers, where they might find some inspirations and useful information. Moreover, as SocialNLP has an aim to make data available to the research community and will provide a platform for researchers to share datasets, AI researchers and NLP researchers can get familiar with the data from each other and access them easily. Fourth, user-generated content in social media is mainly in the form of text. Theories and techniques on artificial intelligence and natural language processing are desired for semantic understanding, accurate search, and efficient processing of social media contents. From the perspective of application, novel online applications involving social media analytics and sentiment analysis, such as emergency management, social recommendation, user behavior analysis, user social community analysis and future prediction, are topics that NLP and AI researchers have paid attention to. In short, hosting SocialNLP workshop in both IJCAI and EMNLP will provide mutually-reinforced benefits for researchers in areas of AI 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 research 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

Disaster Management Using Social Media

  • Modeling global events or human activities based on social media texts
  • Identification and geo-location of social media content
  • Social-based web platform for disaster management
  • Disaster or disease prediction and forecasting
  • Resource allocation using social media
  • Monitoring emergency responses among social crowds
  • Analyzing the diffusion of emergent information
  • Exploiting social media for crisis response and search and rescue activities

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

Paper Submission

SocialNLP @ IJCAI 2016 SocialNLP @ EMNLP 2016
Page Limit Regular Paper: 6 pages
DATA Paper: 5 pages
Regular Paper: 8 pages
DATA Paper: 5 pages
(both allow additional 2 pages for references)
Paper Template IJCAI Formatting Guidelines ACL Style Files
Submission Site SocialNLP 2016 @ Easychair SocialNLP 2016 @ Softconf

SocialNLP review is double-blind. Therefore, please anonymize your submission: do not put the au-thor(s) names or affiliation(s) at the start of the paper, and do not include funding or other acknowl-edgments in papers submitted for review. In addition to regular paper, we call for DATA PAPER this year. A data paper should include the details of the created dataset and an experiment illustrating how to use it. Authors should note it as a data paper using the author field and submit at least partial data as accompanied materials. The created dataset should be able to be downloaded or acquired through an application process freely. If the data paper is accepted, we will list the link for accessing the dataset in the SocialNLP website. Note that the review for data papers is also double-blind and it is authors’ re-sponsibility to avoid revealing their identities.

Papers submitted to this workshop must not have been accepted for publication elsewhere or be under review for another workshop, conference or journal. Papers should be written in English. Each submis-sion will be evaluated by at least 3 program committee members. For SocialNLP@IJCAI-2016, the workshop proceedings will be published in IJCAI Paper Repository. For SocialNLP@EMNLP-2016, the workshop proceedings will be published in ACL Anthology.

To pursue high quality submission, we will have a best paper award of SocialNLP 2016 for both venues. The selection process will depend on not only the review comments/ratings, but also the quality of paper that is rated by paper authors. Selected, expanded versions of papers presented at the workshop will be published in two follow-on Special Issues of Springer Journal of Information Science and Engineering (JISE) and the International Journal of Computational Linguistics and Chinese Language Processing (IJCLCLP).


Please note that at least one registration per paper published is required. At the time of submission of the final camera-ready copy, authors will have to indicate the already registered person for that publication.

Program @ IJCAI

Date: 2016.07.11
Location: Room East

SocialNLP @ IJCAI 2016
09:20-09:30 Opening and Welcome
09:30-10:30 [Keynote Speech] Sensemaking of Events Using Social Media
Yuheng Hu, Assistant Professor, Department of Information and Decision Sciences, University of Illinois at Chicago
Social media platforms such as Twitter, Facebook, and blogs have emerged as valuable - in fact, the de facto - virtual town halls for people to discover, report, share and communicate with others about various types of events. These events range from widely-known events such as the U.S Presidential debate to smaller scale, local events such as a local Halloween block party. During these events, we often witness a large amount of commentary contributed by crowds on social media. This burst of social media responses surges with the"second-screen'' behavior and greatly enriches the user experience when interacting with the event and people's awareness of an event. Monitoring and analyzing this rich and continuous flow of user-generated content can yield unprecedentedly valuable information about the event, since these responses usually offer far more rich and powerful views about the event that mainstream news simply could not achieve. Despite these benefits, social media also tends to be noisy, chaotic, and overwhelming, posing challenges to users in seeking and distilling high-quality content from that noise.

In this talk, I will explore ways to leverage social media as a source of information and analyze events based on their social media responses collectively. I will talk about EventRadar, an event analysis toolbox which is able to identify, enrich, and characterize events using the massive amounts of social media responses. EventRadar contains three automated, scalable tools to handle three core event analysis tasks: Event Characterization, Event Recognition, and Event Understanding. Enabled by EventRadar, it is more feasible to uncover patterns that have not been explored previously and re-validating existing social theories with new evidence. I will talk about how people respond to the event that they are engaged in, and the factors that affect a person's engagement with real-world events. I will conclude the talk with a few open questions on event analysis using social media posts.
Yuheng Hu is an Assistant Professor in the Department of Information and Decision Sciences at College of Business Administration at University of Illinois at Chicago. Prior to joining UIC in 2015, he worked as a Research Staff Member at IBM Research. Yuheng obtained his Ph.D in Computer Science at Arizona State University. His research interests are on the intersection of Social Computing and Data Mining, with a particular focus on analyzing, characterizing and predicting large-scale, time-varying, heterogeneous human behaviors manifested in their online footprints at both individual and collective levels. His research has won several paper awards and frequently featured in major media, including ABC, PBS, the Seattle Times, the Huffington Post, WIRED magazine and so on.
10:30-11:00 Coffee Break
Social Media Session
Injecting Sentiment Information in Context-aware Convolutional Neural Networks PDF
Danilo Croce, Giuseppe Castellucci, and Roberto Basili
Towards a Sentiment Dependent Bayesian Network Classifier for Online Product Reviews PDF
Sylvester Olubolu Orimaye, Zi Yang Pang, and Alvino Mandala Putra Setiawan
Negation Effect on Emotion Analysis in Twitter PDF
Zach Stallbohm, Yang Liu, and Zhongyu Wei
12:30-14:00 Lunch
NLP Session
Cross-Domain Entity Resolution in Social Media PDF
William Campbell, Lin Li, and Charlie Dagli
Resource Creation for Hindi-English Code Mixed Social Media Text PDF
Sakshi Gupta, Piyush Bansal, and Radhika Mamidi
Detecting Code-switching in Moroccan Arabic Social Media PDF
Younes Samih and Wolfgang Maier
Closing Session

Tentative Program @ EMNLP

Date: 2016.11.01
Location: TBA

SocialNLP @ EMNLP 2016
08:50-09:00 Opening and Welcome
09:00-10:00 [Keynote Speech] Social Cues in Conversational Dynamics
Cristian Danescu-Niculescu-Mizil, Assistant Professor, Department of Information Science, Cornell University
Abstract. TBA.
Bio. Cristian Danescu-Niculescu-Mizil is an assistant professor in the information science department at Cornell University. His research aims at developing computational frameworks that can lead to a better understanding of human social behavior, by unlocking the unprecedented potential of the large amounts of natural language data generated online. He is the recipient of several awards, including the WWW 2013 Best Paper Award, a Google Faculty Research Award and a Yahoo! Key Scientific Challenges Award, and his work has been featured in popular-media outlets such as the Wall Street Journal, NBC's The Today Show, NPR, BBC and the New York Times.
Short Paper Session I
Identifying and Categorizing Disaster-Related Tweets
Kevin Stowe, Michael J. Paul, Matha Palmer, Leysia Palen, Kenneth Anderson
Identifying Eyewitness News-worthy Events on Twitter
Erika Doggett, Alejandro Cantarero
10:30-11:00 Coffee Break
Short Paper Session II
Why Do They Leave: Modeling Participation in Online Depression Forums
Farig Sadeque, Ted Pedersen, Thamar Solorio, Prasha Shrestha, Nicolas Rey-Villamizar and Steven Bethard
Twitter at the Grammys: A Social Media Corpus for Entity Linking and Disambiguation
Mark Dredze, Nicholas Andrews and Jay DeYoung
Toward Automatic Understanding of the Function of Affective Language in Support Groups
Amit Navindgi, Caroline Brun, Cecile Boulard Masson, Scott Nowson
Detecting Social Roles in Twitter
Sunghwan Mac Kim, Stephen Wan and Cecile Paris
Identifying Sensible Participants in Online Discussions
Siddharth Jain
12:30-14:00 Lunch
Long Paper Session I
emoji2vec: Learning Emoji Representations from their Description
Ben Eisner, Tim Rocktäschel, Isabelle Augenstein, Matko Bosnjak and Sebastian Riedel
Learning Latent Local Conversation Modes for Predicting Comment Endorsement in Online Discussions
Hao Fang, Hao Cheng and Mari Ostendorf
Witness Identification in Twitter
Rui Fang, Armineh Nourbakhsh, Xiaomo Liu, Sameena Shah and Quanzhi Li
15:30-16:00 Coffee Break / Poster Session and Discussion
Long Paper Session II
How Do I Look? Publicity Mining From Distributed Keyword Representation of Socially Infused News Articles
Yu-Lun Hsieh, Yung-Chun Chang, Chun-Han Chu and Wen-Lian Hsu
Hierarchical Character-Word Models for Language Identification
Aaron Jaech, George Mulcaire, Shobhit Hathi, Mari Ostendorf and Noah A. Smith
Human versus Machine Attention in Document Classification: A Dataset with Crowdsourced Annotations
Nikolaos Pappas and Andrei Popescu-Belis
Award and Closing

Important Dates

SocialNLP @ IJCAI 2016 SocialNLP @ EMNLP 2016
Submission Deadline April 11, 2016
Extended to April 18, 2016
(23:59 Hawaii Standard Time)
August 5, 2016
Extended to August 12, 2016
(23:59 Hawaii Standard Time)
Author Notification May 16, 2016 September 5, 2016
Camera-ready Submission May 30, 2016 September 26, 2016
Workshop Date July 11, 2016 November 1, 2016

Program Committee

  • Zeljko Agic, University of Copenhagen
  • Nikolaos Aletras, Amazon UK
  • Tim Althoff, Stanford University
  • Hadi Amiri, University of Maryland
  • Ion Androutsopoulos, Athens University of Economics and Business
  • Alexandra Balahur, European Commission Joint Research Centre
  • Roberto Basili, University of Rome Tor Vergata
  • Fabrício Benevenuto, Federal University of Minas Gerais
  • Kalina Bontcheva, University of Sheffield
  • Taylor Cassidy, US Army Research Laboratory
  • Berlin Chen, National Taiwan Normal University
  • Hsin-Hsi Chen, National Taiwan University
  • John Chen, Interactions LLC
  • Hai Leong Chieu, DSO National Laboratories
  • Monojit Choudhury, Microsoft Research, India
  • Lei Cui, Microsoft Research
  • Aron Culotta, Illinois Institute of Technology
  • Pradipto Das, Rakuten Institute of Technology
  • Leon Derczynski, The University of Sheffield
  • Marco Dinarelli, Lattice-CNRS
  • Koji Eguchi, Kobe University
  • Michael Elhadad, Ben-Gurion University of the Negev
  • Hugo Jair Escalante, INAOE
  • Wei Gao, Qatar Computing Research Institute
  • Spandana Gella, University of Edinburgh
  • Alastair Gill, King's College London
  • Weiwei Guo, Yahoo! Labs
  • Scott Hale, University of Oxford
  • William Hamilton, Stanford University
  • Bo Han, IBM Research
  • Catherine Havasi, Luminoso, MIT
  • Yulan He, Aston University
  • Michael Heilman, Civis Anlytics
  • Graeme Hirst, University of Toronto
  • John Henderson, MITRE
  • Tuan-Anh Hoang, Singapore Management University
  • Wen-Lian Hsu, Academia Sinica
  • Ruihong Huang, Texas A&M University
  • Ting-Hao Huang, Carnegie Mellon University
  • Iustina Ilisei, Cognizant Technology Solutions Corp.
  • Yangfeng Ji, Georgia Tech
  • Jing Jiang, Singapore Management University
  • Anders Johannsen, University of Copenhagen
  • David Jurgens, Stanford University
  • Nobuhiro Kaji, Yahoo! Japan Corp.
  • Pallika Kanani, Oracle Labs
  • Emre Kiciman, Microsoft Research
  • Dongwoo Kim, ANU
  • Suin Kim, Korea Advanced Institute of Science and Technology
  • Roman Klinger, Univeristy of Stuttgart
  • Lingpeng Kong, Carnegie Mellon University
  • June-Jei Kuo, National Chung Hsing University
  • Tsung-Ting Kuo, University of California, San Diego
  • Patrik Lambert, Universitat Pompeu Fabra
  • Man Lan, East China Normal University
  • Kyumin Lee, Utah State University
  • Sungjin Lee, Yahoo! Labs
  • Haibo Li, Nuance Communications
  • Shou-De Lin, National Taiwan University
  • Yu-Ru Lin, University of Pittsburgh
  • Chuan-Jie Lin, National Taiwan Ocean University
  • Kang Liu, Chinese Academy of Sciences
  • Zhiyuan Liu, Tsinghua University
  • Bin Lu, Google Inc.
  • Zhunchen Luo, China Defense Science and Technology Information Center
  • Bruno Martins, University of Lisbon
  • Diana Maynard, University of Sheffield
  • Karo Moilanen, University of Oxford
  • Manuel Montes-y-Gómez, National Institute of Astrophysics, Optics and Electronics
  • Edward Newell, McGill University
  • Dong Nguyen, University of Twente
  • Scott Nowson, Xerox Research Centre Europe
  • Miles Osborne, Bloomberg
  • George Paliouras, NCSR, Demokritos
  • Harris Papageorgiou, ATHENA RC
  • Michael Paul, University of Colorado Boulder
  • Barbara Plank, University of Copenhagen
  • Stephan Raaijmakers, TNO, The Netherlands
  • Sravana Reddy, Wellesley College
  • Saurav Sahay, Intel Labs
  • Hassan Saif, The Open University
  • Yohei Seki, University of Tsukuba
  • Mário J. Silva, Universidade de Lisboa
  • Yanchuan Sim, Carnegie Mellon University
  • Jan Snajder, University of Zagreb
  • Veselin Stoyanov, Facebook Inc.
  • Carlo Strapparava, FBK-irst
  • Keh-Yih Su, Academia Sinica
  • Hiroya Takamura, Tokyo Institute of Technology
  • Xavier Tannier, Université Paris-Sud, Université Paris-Saclay, LIMSI, CNRS
  • Ming-Feng Tsai, National Chengchi University
  • Paola Velardi, University of Roma La Sapienza
  • Marc Verhagen, Brandeis University
  • Svitlana Volkova, PNNL
  • Xiaojun Wan, Peking University
  • Hsin-Min Wang, Academia Sinica
  • Jenq-Haur Wang, National Taipei University of Technology
  • William Yang Wang, Carnegie Mellon University
  • Ingmar Weber, Qatar Computing Research Institute
  • Albert Weichselbraun, University of Applied Sciences Chur
  • Robert West, Stanford University
  • Janyce Wiebe, University of Pittsburgh
  • Ruifeng Xu, Harbin Institute of Technology
  • Yi Yang, Georgia Tech
  • Yi-Hsuan Yang, Academia Sinica
  • Bei Yu, Syracuse University
  • Liang-Chih Yu, Yuan Ze University
  • Nicholas Jing Yuan, Microsoft Research
  • Zhe Zhang, IBM Watson
  • Hua-Ping Zhang, Beijing Institute of Technology
  • Xin Zhao, Renmin University of China
  • Deyu Zhou, Southeast University
  • Jun Zhu, Tsinghua University


Past SocialNLP


If you are considering submitting to the workshop and have questions regarding the workshop scope or need further information, please do not hesitate to send e-mail to both lwku [AT] and ctli [AT] Thanks!