no code implementations • 16 Nov 2022 • Vibhor Agarwal, Anthony P. Young, Sagar Joglekar, Nishanth Sastry
We evaluate GraphNLI on two such tasks - polarity prediction and misogynistic hate speech detection - and found that our model consistently outperforms all relevant baselines for both tasks.
1 code implementation • 16 Feb 2022 • Vibhor Agarwal, Sagar Joglekar, Anthony P. Young, Nishanth Sastry
We then use these embeddings to predict the polarity relation between a reply and the post it is replying to.
no code implementations • 1 Mar 2021 • Sanja Scepanovic, Luca Maria Aiello, Ke Zhou, Sagar Joglekar, Daniele Quercia
We validated the structure of our taxonomy against the official International Statistical Classification of Diseases and Related Health Problems (ICD-11), finding matches of our clusters with 20 official categories, out of 22.
no code implementations • 28 Jan 2021 • Sanja Šćepanović, Sagar Joglekar, Stephen Law, Daniele Quercia
Back in the 1970s, Jane Jacobs theorized urban vitality and found that there are four conditions required for the promotion of life in cities: diversity of land use, small block sizes, the mix of economic activities, and concentration of people.
no code implementations • 23 Apr 2020 • Pushkal Agarwal, Kiran Garimella, Sagar Joglekar, Nishanth Sastry, Gareth Tyson
In the case of images containing text that cross language barriers, we see that language translation is used to widen the accessibility.
1 code implementation • 12 Sep 2019 • Aravindh Raman, Sagar Joglekar, Emiliano De Cristofaro, Nishanth Sastry, Gareth Tyson
The Decentralised Web (DW) has recently seen a renewed momentum, with a number of DW platforms like Mastodon, Peer-Tube, and Hubzilla gaining increasing traction.
Networking and Internet Architecture Cryptography and Security Computers and Society
1 code implementation • 9 Mar 2018 • Shweta Bhatt, Sagar Joglekar, Shehar Bano, Nishanth Sastry
This paper aims to shed light on alternative news media ecosystems that are believed to have influenced opinions and beliefs by false and/or biased news reporting during the 2016 US Presidential Elections.
Social and Information Networks