First Workshop on Language Technology for Equality, Diversity, Inclusion (LT-EDI-2021) @EACL 2021
(https://sites.google.com/view/lt-edi-2021/home)
Equality, Diversity and Inclusion (EDI) is an important agenda across every field in the world. Language as a major part of communication should be inclusive and treat everyone equally. The internet community that uses language technology has a direct impact on people across the globe. EDI is crucial to make everyone valued and included, so it is necessary to build language technology that serves this purpose. Our workshop brings together researchers to research into inclusivity of gender, racial, sexual orientation, persons with disability, and other minorities in language technologies with the aim to build and use datasets addressing the concerns of EDI.
The broader objective of LT-EDI-2021 will be
To investigate challenges related to language resource creation for EDI.
To promote research in inclusive language technology.
To adopt and adapt appropriate language technology models to suit EDI.
To provide opportunities for researchers from the language technology community from around the world to collaborate with other researchers to identify and bring possible solutions to the challenges of EDI.
We hope that through these engagements we can develop language technology tools to be more inclusive of everyone.
Call for Papers:
Our main theme in this workshop is to promote equality, diversity, and inclusivity in language technologies. We invite researchers and practitioners to submit papers reporting on these issues and datasets to ameliorate the same. We also encourage related qualitative studies. LT-EDI-2021 welcomes theoretical and practical paper submissions on any language that contribute to research in Equality, Diversity and Inclusion. We will particularly encourage studies that address either practical application or resource improvement.
Topics of interest include, but are not limited to:
Corpus development to include EDI
Gender inclusivity in language technology
LGBT inclusivity in language technology
Racial inclusivity in language technology
Persons with disability inclusivity in language technology
Unconscious bias and ways to avoid them in language technologies
Tackling rumors and fake news about gender, racial, and LGBT minorities.
Tackling discrimination against gender, racial, and LGBT minorities.
Important Dates:
Jan 6 : Pre-submission paper due
Jan 18: Workshop Paper due
Feb 18: Notification of Acceptance
Mar 1 : Camera-ready papers due
April 19-20: Workshop Dates
Mentoring: We will follow the ACL SRW mentoring program, since English is not the first language of many of the participating researchers. “The goal of the pre-submission mentor-ship program is to improve the quality of writing and presentation of the researcher's work, not to criticize the work itself. Participation is optional but encouraged. Pre-submission mentor-ship is not anonymous” similar to ACL SRW. Pre-submission paper due : Jan 8, 2021
Submission:
Papers must describe original, completed / in progress and unpublished work. Each submission will be reviewed by three program committee members. Accepted papers will be given up to 8 pages (for full papers), 4 pages (for short papers and posters) in the workshop proceedings, and will be presented as oral paper or poster. Papers should be formatted according to the EACL 2021 style-sheet, which is provided on the website (https://2021.eacl.org/). You can find the EACL-2021 LaTeX template here or download the zip file. Please submit papers in PDF format.
We are seeking submissions under the following category
Full papers (8 pages)
Short papers (work in progress, innovative ideas/proposals, research proposal of students: : 4 page)
Demo (of working online/standalone systems: : 4 page)
For electronic submission of all papers, please use: https://www.softconf.com/eacl2021/LTEDI2021/
Organizers
Bharathi Raja Chakravarthi, Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway
Kalika Bali, Microsoft Research India
John P. McCrae, Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway
Paul Buitelaar, Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway
Manel Zarrouk, Institut Galilée @ University Sorbonne North Paris
Associated Shared Task:
Task 1: Dataton on language resource creation for Equality, Diversity and Inclusivity (EDI).
In many places, supporting diversity and promoting inclusion is still a major issue, as it is in language technology as well. Data created with bias propogrates and makes systems developed using the dataset biased as well [1]. We could describe ‘bias’ as an unfair discrimination against any individual or a group of individuals that occurs systematically in favour of others [2]. In other words, we could also say that Bias occurs when there is systematic unfair discrimination. Bias may be introduced in the data as a result of the following three scenarios:
Pre-existing Bias : Any bias that occurs in institutions, practices and attitude in society
Technical Bias : Any bias that originates from technical constraints and decisions
Emergent Bias: Any bias that occurs when a system designed for one context is applied in another
In this dathon, we propose bringing researchers together to create datasets to be more inclusive not only with respect to gender issues but also racial, sexuality, people with disability etc. The participants will be asked to create language resources or improve existing datasets to deal with EDI in their native language. The participants can create datasets for socio-pragmatics, morphology, syntax etc.
The datathon is to create a new dataset or remediate bias in an already existing dataset. We encourage participant to submit the data statement, dataset and paper describing the dataset. Sample data statements are available here:
https://sites.google.com/uw.edu/data-statements-for-nlp/sample-data-stat... Resources will be evaluated in terms of resource quality and the EDI factors considered. Participants are expected to submit the datasets along with a data statement.
Evaluated on
terms of resource quality
EDI factors
Paper submission
Each team participating in the datathon is expected to submit a short/long paper along with a data statement. The paper should explain the data collection processes and tools used to collect the resource. The methodology/strategy should be documented in such a way that the readers and other researchers are able to replicate the work from the system description paper. Submit the paper and data to lt-edi@insight-centre.org. Deadline is same as workshop deadlines.
References:
[1]Bender, E.M. and Friedman, B., 2018. Data statements for natural language processing: Toward mitigating system bias and enabling better science. Transactions of the Association for Computational Linguistics, 6, pp.587-604.
[2] Friedman, Batya, and Helen Nissenbaum. "Bias in computer systems." ACM Transactions on Information Systems (TOIS) 14.3 (1996): 330-347.
Task 2: Hope Speech Detection for Equality, Diversity and Inclusion
Hope is considered significant for the well-being, recuperation and restoration of human life by health professionals. Hope speech reflects the belief that one can discover pathways to one's desired objectives and become motivated to utilise those pathways[1-5]. Our work aims to change the prevalent way of thinking by moving away from a preoccupation with discrimination, loneliness or the worst things in life to building confidence, support and good qualities based on comments by individuals. The goal of this task is to identify whether a comment contains hope speech or not. The comment/post may contain more than one sentence but the average sentence length of the corpora is 1. Each comment/post is annotated at a comment/post level. This dataset also has class imbalance problems depicting real-world scenarios.
The participants will be provided development, training and test dataset in English, Tamil, and Malayalam. To download the data and participate, go to codalab and click “Participate tab”.
To the best of our knowledge, this is the first shared task on Hope Speech Detection.
Codalab link: https://competitions.codalab.org/competitions/27653
Organizers
Bharathi Raja Chakravarthi, Insight SFI Research Centre for Data Analytics, Data Science Institute, National University of Ireland Galway
Vigneshwaran Muralidaran, School of Computer Science and Informatics, Cardiff University, United Kingdom
Reference:
[1] Harvey Milk. 1997. The hope speech. We are everywhere: A historical sourcebook of gay and lesbian politics,pages 51–53
[2] Edward C. Chang. 1998. Hope, problem-solving ability, and coping in a college student population: Some implications for theory and practice. Journal of Clinical Psychology, 54(7):953–962
[3] Carolyn M. Youssef and Fred Luthans. 2007. Positive organizational behavior in the workplace: The impact of hope, optimism, and resilience. Journal of Management, 33(5):774–80
[4] Rob Cover. 2013. Queer youth resilience: Critiquing the discourse of hope and hopelessness in lgbt suicide representation.M/C Journal, 16(5).
[5]Snyder, C. R., Harris, C., Anderson, J. R., Holleran, S. A., Irving, L. M., Sigmon, S. T., et al.(1991). The will and the ways: Development and validation of an individual-differences measure of hope. Journal of Personality and Social Psychology, 60, 570-585.