The 9th International Workshop on
Natural Language Processing for Social Media
In conjunction with TheWebConf 2021 @ April 16, 2021.
In conjunction with NAACL 2021 @ June 10, 2021.


  • The Program @ NAACL 2021 is released. (2021.06.01)
  • Fake-EmoReact 2021 Challenge, the shared task of SocialNLP@NAACL 2021, is announced!! (2021.04.20)

    Fake news could be spread rapidly from one to another, especially on social media. The misinformation situation is even worse, due to the pandemic of Covid-19. Seeing the high impact of fake news on society, we eager to mitigate the effect of fake news by applying NLP techniques. For the reasons above, We design the Fake-EmoReact challenge.

    We set the goal of this challenge to detect fake news tweets on Twitter as soon as possible from their text, replies, and GIF responses. In this challenge, a total of 209,008 sequential utterances and their fake news labels were provided to the participants who registered for this shared task. GIF response was labeled with the categories of the animated GIFs, which provides emotion category. We have both the textual and visual data for participants to develop models for fake news detection. The challenge: Given unlabeled tweet and its GIF response, predict the label of tweet.

    Read more about the task!

    May 1-3, 2021: Round 1 Practice Phase (08:00 UTC)
    May 6, 2021: Round 1 Evaluation Results Released
    May 28, 2021: Round 2 Evaluation Phase Begins (08:00 UTC)
    May 30, 2021: Round 2 Evaluation Phase End (08:00 UTC)
    June 2, 2021: Round 2 Evaluation Results Released
    June 7, 2021: Technical Report Due
    June 8, 2021: Acceptance and Presentation Mode Notification
    June 10, 2021: Online SocialNLP Workshop and Presentations

  • The deadline of camera-ready version @ NAACL 2021 is postponed to April 19, 2021. (2021.04.12)
  • The Program @ TheWebConf 2021 is released. (2021.04.08)
  • The notification of @ NAACL 2021 is postponed to April 10, 2021. (2021.04.07)
  • The submission site of @ NAACL 2021 is updated to be at Softconf. (2021.03.10)
  • The submission deadline of @ NAACL 2021 is postponed to March 25, 2021. (2021.03.10)
  • Due to the schedule change of @TheWebConf2021's ACM workshop proceedings instructed by workshop chairs, we can extend the submission deadline to February 7, 2021 (23:59, AoE Time Zone). (2021.01.15)
  • The submission deadline of @TheWebConf2021 is postponed to January 18, 2021. (2021.01.05)
  • The important dates of @TheWebConf2021 have been updated according to workshop chair's instructions. (2021.01.05)
  • The error on submission site has been fixed. Please visit EasyChair Platform to make submission. (2021.01.05)
  • SocialNLP 2021 Call for Papers is out. (2020.12.11)
  • SocialNLP 2021 webpage is online. (2020.10.09)

Workshop Description

With the rapid growth of social networks and Web 2.0 services (e.g. Facebook and Twitter), being able to process data come from such platforms has gained much attention in recent years. SocialNLP is a new inter-disciplinary area of natural language processing (NLP) and social computing. We consider three plausible directions of SocialNLP: (1) addressing issues in social computing using NLP techniques; (2) solving NLP problems using information from social networks or social media; and (3) handling new problems related to both social computing and natural language processing.

Several challenges are foreseeable in SocialNLP. First, the message lengths on social media services are usually short (e.g., 140 characters per tweet in Twitter) and thus it is difficult to apply traditional NLP approaches directly. Second, social media contains heterogeneous social information (e.g., tags, friends, followers, endorsements, profiles, and retweets) that should be considered together with the contents for better quality of analysis. Finally, microblogs and the social media contents always involve the interactions among multiple persons with slangs and jargons, and usually require special techniques to distill reasonable information and discover useful knowledge.

To encourage research in the area of SocialNLP, we have organized a SocialNLP SIG-group in AFNLP since 2012 and made it first a yearly now twice a year based workshop series. Through this workshop, we provide a platform for research outcome presentations and head-to-head discussions in the area of SocialNLP, with the hope to combine the insight and experience of prominent researchers from both NLP and social computing fields to jointly contribute to this area.

Seeing the high impact of COVID-19 Pandemic this year, we are thinking about what we and the NLP techniques can do to help mitigate what it did to us. A serious issue which obviously makes the situation even worse is the fake news of Covid-19. For example, the belief on the fake news about drinking pure alcohol helps prevent the infection causes 30 death in Turkey. Considering our workshop's previous participants have developed technologies and systems related to social media data and emotion analysis, we especially design the CovidFake-EmoReact challenge this year.

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
  • Issues on COVID-19 in social media

Information Disorder on Social Media

  • Fake news detection on short texts
  • Cyberbullying detection
  • Hate speech detection
  • Clickbait detection
  • Malicious account detection
  • Robust misinformation detection
  • Flight again machine-generated fake messages
  • Multi-modal fake message detection
  • Spread prediction of disinformation
  • Explainable AI for information disorder

Paper Submission

SocialNLP @ TheWebConf 2021 SocialNLP @ NAACL 2021
Page Limit Regular Paper: 8 pages
DATA Paper: 5 pages
(both includes references)
Regular Paper: 8 pages
DATA Paper: 4 pages
(both allow additional 2 pages for references)
Paper Template ACM Format (sigconf)
ACL Style Files
Submission Site EasyChair Platform Softconf Site

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@ACL-2021, the workshop proceedings will be published in ACL Anthology.

To pursue high quality submission, we will have a best paper award of SocialNLP 2021 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).

Program @ TheWebConf 2021

Date: April 16 (CEST time zone)
MiTeam link: (registration required)

SocialNLP @ TheWebConf 2021
14:00-15:00 [Keynote Speech] Detecting and Countering Misinformation and Sockpuppetry on the Web
Srijan Kumar, Assistant Professor,
CSE, College of Computing at Georgia Institute of Technology.
The web enables people to interact with one another and shape opinion at an unprecedented speed and scale. However, the prevalence of disinformation and malicious users makes the web unsafe and unreliable. In this talk, I will present advances made to improve the trust, safety, and integrity of web and social media platforms. In the first part of the talk, I will present how non-expert citizens counter COVID-19 misinformation on social media. In the second part of the talk, I will discuss our work on how sockpuppets manipulate the discussions on the web. I will end the talk by highlighting the open challenges in the area.
Srijan Kumar is an Assistant Professor at the College of Computing at Georgia Institute of Technology. His research develops data science solutions to address the high-stakes challenges on the web and in the society. He has pioneered the development of user models and network science tools to enhance the well-being and safety of users. His methods are being used in production at Flipkart, India's largest e-commerce platform. He has received several awards including the Facebook Faculty Award, Adobe Faculty Award, ACM SIGKDD Doctoral Dissertation Award runner-up 2018, Larry S. Davis Doctoral Dissertation Award 2018, and 'best of' award from WWW. His research has been the subject of a documentary and covered in popular press, including CNN, The Wall Street Journal, Wired, and New York Magazine. He completed his postdoctoral training at Stanford University, received a Ph.D. in Computer Science from University of Maryland, College Park, and B.Tech. from Indian Institute of Technology, Kharagpur.
15:00-15:10 Break
Paper Session I
[20 Minutes] Are Your Friends Also Haters? Identification of Hater Networks on Social Media
Maximilian Wich, Melissa Breitinger, Wienke Strathern, Marlena Naimarevic, Georg Groh and Jürgen Pfeffer.

[20 Minutes] Tweet-aware News Summarization with Dual-Attention Mechanism
Xin Zheng, Aixin Sun and Karthik Muthuswamy.

[20 Minutes] Emotion-Aware Event Summarization in Microblogs
Rrubaa Panchendrarajan, Wynne Hsu and Mong Li Lee.

[20 Minutes] Response Selection for a Virtual Counsellor
John Lee and Kent Leung.

16:30-16:40 Break
Paper Session II
[20 Minutes] A Comparative Study of Using Pre-trained Language Models forToxic Comment Classification
Zhixue Zhao, Ziqi Zhang and Frank Hopfgartner.

[20 Minutes] Affect Classification in Tweets using Multitask Deep Neural Networks
Seema Nagar, Achintya Shankhdhar, Ferdous Ahmed Barbhuiya and Kuntal Dey.

[20 Minutes] Hate, Obscenity, and Insults: Measuring the Exposure of Children to Inappropriate Comments in YouTube
Sultan Alshamrani, Ahmed Abusnaina, Mohammed Abuhamad, Daehun Nyang and David Mohaisen.

Program @ NAACL 2021

Date: June 10 (Time zone: GMT-7)

SocialNLP @ NAACL 2021
09:00-09:10 Opening
09:10-10:00 [Keynote Speech #1] Joint Models for Social, Behavioral and Textual Information
Dan Goldwasser, Associate Professor
Department of Computer Science at Purdue University.
Understanding natural language communication often requires context, such as the speakers' backgrounds and social conventions, however, when it comes to computationally modeling these interactions, we typically ignore their broader context and analyze the text in isolation. In this talk, I will review on-going work demonstrating the importance of holistically modeling behavioral, social, and textual information. I will focus on several NLP problems, including political discourse analysis on Twitter and partisan news detection, and discuss how jointly modeling text and social behavior can help reduce the supervision effort and provide a better representation for language understanding tasks.
10:00-10:10 Coffee Break
Technical Session 1: Sentiment, Reviews, and Comments
Analysis of Nuanced Stances and Sentiment Towards Entities of US Politicians through the Lens of Moral Foundation Theory
Shamik Roy and Dan Goldwasser
Content-based Stance Classification of Tweets about the 2020 Italian Constitutional Referendum
Marco Di Giovanni and Marco Brambilla
A Case Study of In-House Competition for Ranking Constructive Comments in a News Service
Hayato Kobayashi, Hiroaki Taguchi, Yoshimune Tabuchi, Chahine Koleejan, Ken Kobayashi, Soichiro Fujita, Kazuma Murao, Takeshi Masuyama, Taichi Yatsuka, Manabu Okumura and Satoshi Sekine
Quantifying the Effects of COVID-19 on Restaurant Reviews
Ivy Cao, Zizhou Liu, Giannis Karamanolakis, Daniel Hsu and Luis Gravano
Technical Session 2: Inappropriate Language (1)
Assessing Cognitive Linguistic Influences in the Assignment of Blame
Karen Zhou, Ana Smith and Lillian Lee
Evaluating Deception Detection Model Robustness To Linguistic Variation
Maria Glenski, Ellyn Ayton, Robin Cosbey, Dustin Arendt and Svitlana Volkova
11:40-12:40 Lunch Break, Poster and Fake-EmoReact Challenge
12:40-13:40 [Keynote Speech #2] Social Information Extraction: A House Built on Sand
Tim Weninger, Frank M. Freimann Collegiate Associate Professor
Department of CSE, College of Engineering, University of Notre Dame.
Creating systems to digest and understand the massive amounts of data from social media has become a hot research topic. Social media data can be difficult to analyze since it is often without labels or structures. Extracting and generating labels are essential to mining and understanding the social media data. The focus of my talk will be on extracting and analyzing text labels on social media. In the first work, we extract and analyze self-contained labels on Reddit, under AITA (Am I The Asshole ) subreddit. Different from most academic analysis on hate speech and misinformation, we look at how users cast moral judgements of one another. In the second work, we discuss our post hoc analysis of existing annotated labels and machine learning generated labels on entity linking tasks. Surprisingly, we find predictions from entity linking models are accepted as correct more often than the ground truth labels of the datasets.
Technical Session 3: Inappropriate Language (2)
Reconsidering Annotator Disagreement about Racist Language: Noise or Signal?
Savannah Larimore, Ian Kennedy, Breon Haskett and Alina Arseniev-Koehler
Understanding and Interpreting the Impact of User Context in Hate Speech Detection
Edoardo Mosca, Maximilian Wich and Georg Groh
Self-Contextualized Attention for Abusive Language Identification
Horacio Jarquín-Vásquez, Hugo Jair Escalante and Manuel Montes
Unsupervised Domain Adaptation in Cross-corpora Abusive Language Detection
Tulika Bose, Irina Illina and Dominique Fohr
14:40-14:50 Coffee Break
Technical Session 4: Personality and Demographics
Using Noisy Self-Reports to Predict Twitter User Demographics
Zach Wood-Doughty, Paiheng Xu, Xiao Liu and Mark Dredze
PANDORA Talks: Personality and Demographics on Reddit
Matej Gjurkovi´c, Mladen Karan, Iva Vukojevi´c, Mihaela Bošnjak and Jan Snajder
Room to Grow: Understanding Personal Characteristics Behind Self Improvement Using Social Media
MeiXing Dong, Xueming Xu, Yiwei Zhang, Ian Stewart and Rada Mihalcea
Technical Session 5: Contexts and Perspectives
Mitigating Temporal-Drift: A Simple Approach to Keep NER Models Crisp
Shuguang Chen, Leonardo Neves and Thamar Solorio
Jujeop: Korean Puns for K-pop Stars on Social Media
Soyoung Oh, JISU KIM, Seungpeel Lee and Eunil Park
Identifying Distributional Perspectives from Colingual Groups
Yufei Tian, Tuhin Chakrabarty, Fred Morstatter and Nanyun Peng
16:20-16:30 Closing

Important Dates

SocialNLP @ TheWebConf 2021 SocialNLP @ NAACL 2021
Submission Deadline January 11, 2021
Extended to January 18, 2021
Extended to February 7, 2021 (AoE Time Zone)
March 15, 2021
Extended to March 25, 2021
Author Notification January 27, 2021
Extended to February 21, 2021
April 15, 2021
Modified to April 10, 2021
Camera-ready Submission January 31, 2021
Extended to February 28, 2021
April 15, 2021
Extended to April 19, 2021
Workshop Date April 16, 2021 June 10, 2021

Program Committee

  • Khalid Al Khatib, Leipzig University
  • Milad Alshomary, Paderborn University
  • Silvio Amir, Northeastern University
  • Guozhen An, City University of New York
  • Ebrahim Bagheri, Ryerson University
  • Sabine Bergler, Concordia University
  • Laura Biester, University of Michigan
  • Victoria Bobicev, Technical University of Moldova
  • Caroline Brun, Institut NeuroMyoGène, Lyon
  • Erik Cambria, Nanyang Technological University
  • Paula Carvalho, UT Austin, Portugal CoLab
  • Yung-Chun Chang, Taipei Medical University
  • Yue Chen, Indiana University
  • Kuan-Yu Chen, National Taiwan University of Science and Technology
  • Zhuang Chen, WuHan University
  • Hai Leong Chieu, DSO National Laboratories
  • Patricia Chiril, Paul Sabatier University
  • Oana Cocarascu, King's College London
  • Danilo Croce, University of Roma, Tor Vergata
  • Lei Cui, Microsoft Research
  • Daniel Dakota, Uppsala University
  • Pradipto Das, Rakuten USA
  • Min-Yuh Day, National Taipei University
  • Anne Dirkson, Leiden University
  • MeiXing Dong, University of Michigan
  • Rory Duthie, University of Dundee
  • Koji Eguchi, Hiroshima University
  • Wassim El-Hajj, American University of Beirut
  • Elisabetta Fersini, University of Milano-Bicocca
  • Lucie Flek, Philipps University of Marburg, TU Darmstadt
  • Andrea Galassi, Università di Bologna
  • Aparna Garimella, Adobe Inc
  • Alexander Gelbukh, Instituto Politécnico Nacional
  • Marco Guerini, Fondazione Bruno Kessler
  • Tunga Güngör, Bogazici University
  • Loitongbam Gyanendro Singh, IIT Guwahati
  • Hatem Haddad, iCompass
  • Chenyang Huang, University of Alberta
  • Hen-Hsen Huang, National Chengchi University
  • Kokil Jaidka, National University of Singapore
  • Charles Jochim, IBM Research - Europe
  • Xincheng Ju, Soochow University
  • Pallika Kanani, Oracle Labs
  • Sundong Kim, Institute for Basic Science, Korea
  • Lun-Wei Ku, Institute of Information Science, Academia Sinica
  • Tsung-Ting Kuo, University of California San Diego
  • June-Jei Kuo, National Chung Hsing University
  • Lung-Hao Lee, National Central University
  • Yang Li, Northwestern Polytechnical University
  • Yingjie Li, University of Illinois at Chicago
  • Yang Li, Northeast Electric Power University
  • Peiqin Lin, Sun Yat-sen University
  • Chuan-Jie Lin, National Taiwan Ocean University
  • Marco Lippi, Università di Modena e Reggio Emilia
  • Pengfei Liu, SpeechX Limited
  • Avinash Madasu, Samsung R & D Institute Bangalore
  • Eugenio Martínez-Cámara, Universidad de Granada
  • Bruno Martins, University of Lisbon
  • Sahisnu Mazumder, University of Illinois at Chicago
  • Manuel Montes, INAOE, Mexico
  • Véronique MORICEAU, IRIT, Université de Toulouse
  • Hamdy Mubarak, Qatar Computing Research Institute QCRI
  • Nona Naderi, Bibliomics and Text Mining Group
  • Jose Ochoa-Luna, Universidad Catolica San Pablo
  • Endang Wahyu Pamungkas, Universita Degli Studi di Torino
  • Kunwoo Park, Soongsil University
  • Haris Papageorgiou, ATHENA Research and Innovation Center
  • Georgios Petasis, National Center for Scientific Research Demokritos
  • Omid Rohanian, University of Oxford
  • Saurav Sahay, Georgia Institute of Technology
  • Mohammad Salameh, University of Alberta
  • Annika Marie Schoene, University of Manchester
  • Boaz Shmueli, National Tsing Hua University and Institute of Information Science, Academia Sinica
  • Abu Awal Md Shoeb, Rutgers University
  • Karandeep Singh, Institute for Basic Science, Korea
  • Priyanka Sinha, Tata Consultancy Services
  • Irena Spasic, Cardiff University
  • Xavier Tannier, Sorbonne Université, INSERM, LIMICS
  • Paolo Torroni, University of Bologna
  • Amine Trabelsi, University of Alberta
  • Enrica Troiano, University of Stuttgart
  • Paola Velardi, Sapienza University of Roma
  • Jenq-Haur Wang, National Taipei University of Technology
  • Jingjing Wang, Tsinghua University
  • Hsin-Min Wang, Academia Sinica
  • Hao Wang, Southwest Jiaotong University
  • Ingmar Weber, Qatar Computing Research Institute QCRI
  • Steven Wilson, The University of Edinburgh
  • Zhen Wu, Nanjing University
  • Shih-Hung Wu, Chaoyang University of Technology
  • Frank Xing, Nanyang Technological University
  • Lu Xu, Singapore University of Technology and Design
  • Jun Yang, Nanjing University
  • Zixiaofan Yang, Columbia University
  • Diyi Yang, Georgia Institute of Technology
  • Liang-Chih Yu, Yuan Ze University
  • Zhe Zhang, IBM
  • Lei Zhang, University of Illinois at Chicago
  • Bowen Zhang, Harbin Institute of Technology
  • Dongyu Zhang, Dalian University of Technology
  • Zhiqiang Zhong, University of Luxembourg
  • Qi Zhang, Fudan University
  • Fei Zhao, Nanjing 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 chengte [AT] Thanks!