[Sigwac] TRAC 2022: Second CFP and Shared Task Participation (COLING 2022 Workshop)

[Ritesh Kumar]

*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.*

On Mon, May 16, 2022 at 12:31 PM Ritesh Kumar <ritesh.lists at gmail.com>
wrote:

> *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 at gmail.com.
>
> Looking forward to your participation!
>
>