Seminars @ DS@UP🚀 - Syed Ishtiaque Ahmed - 26 Nov 2021 - 3 PM SAST

4 views
Skip to first unread message

Vukosi Marivate

unread,
Nov 21, 2021, 7:20:44 AM (8 days ago) Nov 21
to mlds-...@googlegroups.com, masakh...@googlegroups.com

Seminars @ DS@UP🚀 - 2021 Data Science for Society Seminar Series #DS4SocietySeminar

It was just yesterday when we started this year's seminar series. We are now at the final speaker for the 2021 Season. 

Overall Schedule

 

Date Time [SAST] Speaker Organisation Title
18/08/2021 09:00 Felipe Melo ABSA Bank Pattern Extraction in Marketing [Video + Material]
03/09/2021 15:00 Ernest Mwebaze Sunbird.ai Environmental urban noise prediction for Kampala city [Video + Material]
23/09/2021 09:00 Emily Muller Imperial College London Measuring the urban environment using street view imagery [Video + Material]
15/10/2021 15:00 Timnit Gebru   On the dangers of stochastic parrots [Video + Material]
05/11/2021 09:00 Postponed Postponed Postponed to 2022
26/11/2021 15:00 Syed Ishtiaque Ahmed University of Toronto Addressing anti-Asian COVID-related stigma in online communities

Our last speaker for 2021 - 26 November 2021
  • Topic: Anti-Asian COVID-related Hate Speech and Stigma on Twitter: Dataset Creation to Algorithmic Detection
  • Speaker: Syed Ishtiaque Ahmed
  • Sign Up: RSVP
  • Date: 26 November 2021
  • Time: 3:00PM-4:00PM SAST

Abstract

Since the advent of the COVID19 pandemic, individuals of Asian descent have been the subject of stigma and hate speech in both offline and online communities. One of the major venues for encountering such unfair attacks is social networks such as Twitter. In this study, we introduce a dataset of tweets containing sensitive opinions/news relevant to anti-Asian hate speech and stigma. This dataset can be used as a benchmark for further qualitative and quantitative research and analysis around this issue. To showcase the challenges of algorithmic detection of anti-Asian hate speech, we have also developed machine learning models which detect tweets containing COVID-related stigma and hate speech with the best accuracy of 76%, and therefore, can be used for automatic elimination of such behaviour in online communities. We believe this contribution significantly reduces the unfair stigma, hate speech, and discrimination against Asian people during the pandemic, as well as the post-COVID19 times.

Author Bio

Syed Ishtiaque Ahmed is an Assistant Professor of Computer Science at the University of Toronto, and the Director of the ‘Third Space'' research group. His research focuses on the design challenges around strengthening the ‘voices’ or marginalized communities around the world. He conducted ethnography and built technologies with many underprivileged communities in Bangladesh, India, Pakistan, Iran, Iraq, Turkey, China, Canada, and the US. Ishtiaque received his PhD and Masters from Cornell University in the USA, and his Bachelor from BUET in Bangladesh. He received the International Fulbright Science and Technology Fellowship, Fulbright Centennial Fellowship, and Schwartz Reisman Institute Fellowship among others. His research has been funded by all three branches of Canadian tri-council research (NSERC, CIHR, SSHRC), NSF, NIH, Google, Microsoft, Facebook, Intel, Samsung, the World Bank, UNICEF, and UNDP, among others.

The seminars are hosted by the Data Science for Social Impact Research Group, in the Department of Computer Science at the University of Pretoria.

If you have any questions, suggestions or comments, feel free to contact Thapelo Sindane sindane...@tuks.co.za
DS@UP 🚀 by Vukosi Marivate
Lynnwood Road Pretoria, Gauteng South Africa

Delivered by
TinyLetter


This message and attachments are subject to a disclaimer.
Please refer to http://upnet.up.ac.za/services/it/documentation/docs/004167.pdf 
for full details.
Reply all
Reply to author
Forward
0 new messages