*For this iteration of the shared task, we especially encourage those who participated or have trained models on TRAC - 2018 and /or TRAC - 2020 Shared Task datasets to submit the predictions of their earlier models on our current test set. They are, of course, free to submit predictions on new models / current datasets as well.*
*3rd Workshop on Threat, Aggression and Cyberbullying (TRAC - 2022)*
& *Shared Tasks on Bias, Threat and Aggression Identification in Context* Co-located with COLING 2022, October 12 - 17, 2022 Gyeongju, the Republic of Korea
*Second Call for Papers and Shared Task Participation*
*Workshop Website*: https://sites.google.com/view/trac2022/home *Paper Submission*: https://www.softconf.com/coling2022/TRAC-2022/ *Shared Task Website:* https://codalab.lisn.upsaclay.fr/competitions/4753
*Submission Deadline*: July 11, 2022 (Regular) / July 31, 2022 (ACL ARR)
As in the earlier editions of the workshop, TRAC-2022 will focus on the applications of NLP, ML and pragmatic studies on aggression and impoliteness to tackle these issues. We invite *long (8 pages)* and *short papers (4 pages)* as well as *position papers* and opinion pieces (5 - 20 pages), *demo proposals* and *non-archival extended abstracts* (2 pages) based on, but not limited to, any of the following themes from academic researchers, industry and any other group / team working in the area.
- Theories and models of aggression and conflict in language.
- Cyberbullying, threatening, hateful, aggressive and abusive language
on the web.
- Multilingualism and aggression.
- Resource Development - Corpora, Annotation Guidelines and Best
Practices for threat and aggression detection.
- Computational Models and Methods for aggression, hate speech and
offensive language detection in text and speech.
- Detection of threats and bullying on the web.
- Automatic censorship and moderation: ethical, legal and
technological issues and challenges.
*Shared Tasks* TRAC-2022 will include two novel shared tasks:
*Task 1: Bias, Threat and Aggression Identification in Context* The first shared task will be a structured prediction task for recognising (a) Aggression, Gender Bias, Racial Bias, Religious Intolerance and Bias and Casteist Bias on social media and (b) the "discursive role" of a given comment in the context of the previous comment(s). The participants will be given a "thread" of comments with information about the presence of different kinds of biases and threats (viz. gender bias, gendered threat and none, etc) and its discursive relationship to the previous comment as well as the original post (viz. attack, abet, defend, counter-speech and gaslighting). In a series / thread of comments, participants will be required to predict the presence of aggression and bias of each comment, possibly making use of the context.
*Task 2: Generalising across domains - COVID-19* For this sub-task, the test set will be sampled from the COVID-19 related conversation, annotated with levels of aggression, offensiveness and hate speech. Across the globe, during the pandemic, we have seen various kinds of novel aggressive and biased conversation on social media - in fact, in some cases there was massive escalation of religious and other kinds of intolerance and polarisation. The participants of TRAC-1 and TRAC-2 shared tasks are especially encouraged to submit the predictions their their earlier models on this test set. They may also train new models jointly on both the datasets. Those who didn't participate in earlier tasks are also invited to submit the predictions for this task by training models on the two datasets and are encouraged to submit the predictions on the respective test sets of the earlier tasks along with the predictions on the current dataset (to enable comparison). New participants may also use TRAC-1 or TRAC-2 dataset or a combination of the two for building the models. The aim of the task is to evaluate the generalisability of our systems in unexpected and novel situations.
For participation, visit the Codalab website - https://codalab.lisn.upsaclay.fr/competitions/4753
For any clarifications, contact coling.aggression@gmail.com.
Looking forward to your participation!