New Delhi :
IIT Roorkee’s alumnus Richi Nayak & her colleague Mohammad Abdul Bashar have developed an algorithm to understand the content, context, & intent behind social media posts. It aims to identify and report misogynistic posts on Social Media. The COVID-19 lockdown witnessed a spurt in incidences of online harassment and domestic violence against women as people are spending more time on the Internet.
.@iitroorkee‘s alumnus Richi Nayak & her colleague Mohammad Abdul Bashar have developed an algorithm to understand the content, context, & intent behind #socialmedia posts. The research will help detect and report abusive content on social media. More: https://t.co/mQC8zzAukS pic.twitter.com/amRd0WxaLK
— Dr. Ramesh Pokhriyal Nishank (@DrRPNishank) September 26, 2020
Private Images without consent –
Web Foundation survey highlights that 52% of young women and girls admitted that they have experienced online abuse, including threatening messages, sexual harassment, and the sharing of private images without consent.
Research Focusses on the Training –
Richi, who has been exploring to leverage her expertise in machine learning to solve a social issue, is of the view that detecting abusive content targeting women will make them safer online. Her research focusses on the training of models with datasets like Wikipedia and subsequently training it is somewhat abusive language through user review data. It also trained the model on a large dataset of tweets.
Making lives brighter for women –
Besides equipping it with linguistic capability, the researchers taught it to distinguish between misogynistic and non-misogynistic tweets. The research demonstrates the use of STEM knowledge to address societal issues and her endeavor towards making lives brighter for women. Social Media is a Boon as well as a crush. While using social media, everyone should have to be alert about the sort of information shared with people on different platforms.