Posts, News, and Events

June 2022

The lab has received funding from two agencies to continue our research!! 🥳

June 2022






New funding from OBVIA to carry out research on women representation in Québec media during the Covid-19 pandemic. We look forward to a collaboration with colleagues at Université Laval!

February 2022

A summary of our contributions on the Gender Gap Tracker:
1. Dashboards and code:

2. Op-eds and commentary:

3. Academic papers

October 2021

Op-ed on the Gender Gap Tracker and its third birthday:

And a more expanded blog post with more details, publications, and statistics:

October 2021

Op-ed alert! In this piece for Policy Options, the magazine of the Institute for Research on Public Policy, Maite Taboada argues that online toxicity has become banal, something we do without thinking.

September 2021

Op-ed on the language of fake news, in Items, the journal of the Social Sciences Research Council:

August 2021

Our paper received the Test of Time Award from the Association from Computational Linguistics!!!

The paper: Taboada, M., J. Brooke, M. Tofiloski, K. Voll and M. Stede (2011) Lexicon-Based Methods for Sentiment Analysis. Computational Linguistics 37 (2): 267-307.

The Test of Time Award recognizes "papers that have had long-lasting influence on the field of Natural Language Processing and Computational Linguistics."

Citation, from the video of the award ceremony: “This paper shows how a lexicon-based approach can be effective for sentiment analysis, and more importantly, also stable and portable across domains. Despite the current dominance of learning-based methods, lexicon-based methods for sentiment analysis keep being relevant, particularly in new domains where large training data isn’t available and where portability is crucial.”

June 2021

An update on our project about online news comments. Three more papers (#8, #9, and #10 below) on news comments and a summary of our findings:

  1. Raw data
  2. Paper describing the raw data (with small annotations)
  3. Annotated data (12,000 comments), in collaboration with Jigsaw
  4. Paper describing the large-scale annotation
  5. Register analysis: Are news comments like conversations? (tl;dr: NO)
  6. Subjectivity analysis: How complex are news comments vs. opinion articles? (tl;dr: it's complex)
  7. Constructiveness and toxicity across 3 newspapers:
  8. NEW!!! Register analysis, again. If not like conversation, what are comments like? (Answer: a hybrid register):
  9. NEW!!! Appraisal analysis. Comments are very negative. They tend to express evaluation as Judgement or Appreciation (rather than Affect).
  10. NEW!!! Concessive relations in comments. Concessions have an interpersonal function and are used for evaluation and argumentation, especially in constructive comments.

We have learned a lot about online news comments. Mostly, that they are very complex and more like essays than casual conversation.

May 2021

January 2021

We have been working for almost 3 years now on a project analyzing the gender gap in Canadian media. We have created a  summary dashboard with overall statistics and a research dashboard analyzing topics and top-quoted sources. We can also now share the great news that a research paper on the Gender Gap Tracker has been published!

Our findings:

  1. In 2 years of Canadian news media, the percentage of women quoted is regularly below 30%
  2. Women authors quote more women
  3. Politicians dominate in the news
  4. NLP can help us find these patterns in data

November 2020

Op-ed on women quoted during COVID-19:

November 2020

Op-ed by Lucas Chambers and Maite Taboada on media coverage of elections:

September 2020

The lab has been busy analyzing news comments. Here, all in one place, are the papers and the data that we have produced:

  1. Raw data
  2. Paper describing the raw data (with small annotations)
  3. Annotated data
  4. Paper describing the large-scale annotation
  5. Register analysis: Are news comments like conversations? (tl;dr: NO)
  6. Subjectivity analysis: How complex are news comments vs. opinion articles? (tl;dr: it's complex)

March 2020

Fatemeh Torabi Asr just won the SFU President’s Emerging Thought Leader Newsmaker of the Year Award for 2019! We are so proud of her! 

You can read the SFU press release about her award, and the story she wrote about her research on misinformation and fake news, which has reached almost 69,000 reads.

Congratulations, Fatemeh!

March 2020

December 2019

Maite was featured in the WWEST "Best of the West" podcast. WWEST is the Westcoast Women in Engineering, Science and Technology, an organization devoted to promoting increased participation of women in STEM.

November 2019

We analyzed more than 1.5 million comments from 3 news organizations. We found more constructive comments than we expected, that toxicity happens equally across topics and that some news outlets have better commenters than others. The full story:
- Gautam, V. and M. Taboada (2019) Constructiveness and Toxicity in Online News Comments. Report. Simon Fraser University. November 2019.

We also published a short version as an op-ed for The Tyee:

- Gautam, V. and M. Taboada. Hey Tyee Commenters! Scholars Studied You. Here's What They Found. The Tyee (online). November 6, 2019.

November 2019

SOCC, the SFU Opinion and Comments Corpus, has been available online for a while. Now the paper describing it is also online:
- Kolhatkar, V.,H. Wu, L. Cavasso, E. Francis, K. Shukla and M. Taboada (to appear) The SFU Opinion and Comments Corpus: A corpus for the analysis of online news comments. Corpus Pragmatics.

September 2019

Maite is participating in a project that studies online abuse against candidates in the 2019 Canadian federal election, with Heidi Tworek from the University of British Columbia as principal investigator:

Preliminary results of the analysis will be made available early in 2020.

August 2019

Discourse Processing Lab postdoc Fatemeh Torabi Asr publishes an article on the lab's fake news research

June 2019

Maite discusses the Gender Gap Tracker in Spanish:

May 2019

Paper on data quality for misinformation detection now available, open access:

Asr, F.T. and M. Taboada (2019) Big data and quality data for fake news and misinformation detection. Big Data & Society January-June 2019:1-14.

Paper too long to read? There's a video abstract!

March 2019

The lab participated again in the BCTech Summit, showcasing the Gender Gap Tracker.

See a summary of SFU's presence at the Summit.

February 2019

We launched the Gender Gap Tracker in Ottawa!

Maite attended this fabulous event with Maryam Monsef, Minister for Women and Gender Equality and Dr. Joy Johnson, SFU's VP Research, hosted by Shari Graydon of Informed Opinions.

The Gender Gap Tracker, developed within our lab with Informed Opinions, monitors the proportion of women and men quoted in news stories in mainstream Canadian media (in English).

We are having great media coverage for this event. You can check the Conversation piece for an explanation of the tracker, and see other media mentions:
- Tracking the gender gap in Canadian media (The Conversation)
- Online tool gives media outlets incentive to achieve gender parity (The Toronto Star)
- SFU partners with Informed Opinions to create Gender Gap Tracker (SFU News)
- In numbers there is strength (Ottawa Citizen and Montreal Gazette)

January 2019

A short video about Maite's research, especially on sentiment analysis.

Fall 2018

We are pleased to welcome two visiting professors to our lab. María de los Ángeles Gómez-González from the University of Santiago de Compostela will be visiting July-December 2018. Cliff Goddard from Griffith University will be at SFU October-November 2018. Welcome!

July 31, 2018

Emilie Francis successfully defended her M.A. Thesis: "Misinfowars: A Linguistic Analysis of Deceptive and Credible News". Congratulations!

June 22, 2018

The Discourse Lab is hosting a talk by visiting researcher Maite Martín.

Title: Affective and Social Computing in Spanish using Human Language Technologies
: Maite Martín, Universidad de Jaén (Spain)
Friday, June 22, 1 pm
: RCB 7402

Abstract: In this talk I will present some past projects and work in progress in which my research group SINAI (Sistemas INteligentes de Acceso a la Información – Intelligent systems for information access) is involved. Our area of specialization focuses on the development of techniques and tools to solve problems related to Human Language Technologies (HLT). I will briefly discuss our research oriented to Information Retrieval Systems (IRS) mainly in the biomedical domain. We are integrating heterogenous sources of medical and general information (UMLS, Google, SciELO, Dbpedia…) in order to improve the final IRS. I will also highlight the work we have done in the field of affective computing, mainly focused on Spanish and on the social web. Although lot of work has been already done in opinion mining, we think the real challenge is to recognize and analyse emotion expressed in textual documents. Finally, I describe future projects related to early detection of mental health problems (depression, anxiety, cyberbullying…) by analysing the textual information written in social networks. I will show some demos implemented by SINAI.

Short Bio
Dr. Maite Martín is Associate Professor in the Computer Science department of the University of Jaén (Spain). She received her Master's degree in Computer Science at the University of Granada, and her PhD in Computer Science at the University of Málaga. She has been teaching different courses at the University since 1995. She has been a member of the research group SINAI (Sistemas INteligentes de Acceso a la Información – Intelligent systems for information access) since 2000. Her scientific interests include several areas related to Human Language Technologies such as Information Retrieval, Machine Learning, Text Mining and Sentiment Analysis. She has been a member of programme committees of several international and national conferences. In addition, she has participated in more than 30 national research projects serving as lead researcher in some of them. She has published more than a hundred conference papers, journal papers, books and book chapters. Martín is the current treasurer of the Spanish Society of Natural Language Processing (SEPLN – Sociedad Española para el Procesamiento del Lenguaje Natural). She is editor of a number of issues of the journal Procesamiento de Lenguaje Natural (Natural Language Processing). She has also been an invited speaker at several conferences.

May 2018





We participated in the BCTech Summit! We did demos of our two systems, content moderation and fake news detection. You can try them too!

May 2018

A couple of interviews on trolls and social media:

May 2018

Article in The Conversation about our research on online news comments. Trolls, toxicity and construtive conversations.

May 2018

Maite is part of a panel discussing the documentary The Cleaners, about content moderation in social media.

April 2018

SFU News story on our research.

February 2018

Jon Alkorta is a visiting PhD researcher from the University of the Basque Country in Spain. He will be in the lab between February and May, doing research on rhetorical relations and sentiment in Basque.

January 2018

We have just released the SFU Opinion and Comments Corpus (SOCC), a corpus for the analysis of online news comments. Our corpus contains comments and the articles from which the comments originated. The articles are all opinion articles, not hard news articles. The corpus is larger than any other currently available comments corpora, and has been collected with attention to preserving reply structures and other metadata. In addition to the raw corpus, we also present annotations for four different phenomena: constructiveness, toxicity, negation and its scope, and appraisal.

Full details, and download link, are available from our GitHub project page:

For more information about this work, please see our papers.

Varada Kolhatkar (
Maite Taboada (

November 15, 2017

Our postdoctoral researcher, Katharina Ehret, has been featured in an article on the Faculty of Arts and Social Sciences webpage.

Postdoctoral researcher in linguistics, Katharina Ehret, studies why online comments matter

October 18, 2017

Visiting Researcher

Dr. Cliff Goddard from Griffith University in Australia is visiting the Discourse Lab between October 18 and November 10. Dr. Goddard is a long-time collaborator, and is here thanks to an SFU-Griffith Collaborative Travel Grant.

September 2017

The lab has grown! We have two new undergraduate students, a new master's student, and two new postdocs. It'll be a busy semester!

June 30, 2017

Speaker: Muhammad Abdul-Mageed, Assistant Professor of Information Science in the iSchool at UBC.

Abstract: Accurate detection of emotion from natural language has applications ranging from building emotional chatbots to better understanding individuals and their lives. However, progress on emotion detection has been hampered by the absence of large labeled datasets. In this work, we build a very large dataset for fine-grained emotions and develop deep learning models on it. We achieve a new state-of-the-art on 24 fine-grained types of emotions (with an average accuracy of 87.58%). We also extend the task beyond emotion types to model Robert Plutchik’s 8 primary emotion dimensions, acquiring a superior accuracy of 95.68%.

May 2017

Sonya Chik will be a visiting PhD researcher in the lab until August. She is conducting cross-linguistic research on socio-semiotic processes in privacy policies, using a systemic-functional lingusitics approach.

February 24, 2017

Presentation on Spark:

-- MapReduce
-- Spark dataframe udf
-- search engine, Spark GraphFrame
-- Spark MLLIB, Scikit Learn
-- Spark pipeline with coreNLP

Installation instructions for WebAnno

January 20, 2017

Speaker: Enamul Hoque

Abstract: Analyzing and gaining insights from a large amount of online conversations can be quite challenging for a user, especially when the discussions become very long. During my doctoral research, I have focused on integrating Information Visualization (InfoVis) with Natural Language Processing (NLP) techniques to better support the user’s task of exploring and analyzing conversations. For this purpose, I have designed a visual text analytics system that supports the user exploration, starting from a possibly large set of conversations, then narrowing down to a subset of conversations, and eventually drilling-down to a set of comments of one conversation. Our evaluations through case studies with domain experts and a formal user study with regular blog readers illustrate the potential benefits of our approach, when compared to a traditional blog reading interface.