activity
20202025
most citedExploring multi-task multi-lingual learning of transformer models for hate speech and offensive speech identification in social media

21 citations · 24 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DL2025

Revisiting gender bias research in bibliometrics: Standardizing methodological variability using Scholarly Data Analysis (SoDA) Cards

HaeJin Lee, Shubhanshu Mishra, Apratim Mishra +3

Gender biases in scholarly metrics remain a persistent concern, despite numerous bibliometric studies exploring their presence and absence across productivity, impact, acknowledgme…

cs.CL2024

Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions

Zhiwen You, HaeJin Lee, Shubhanshu Mishra +4

Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can…

cs.CL202121 cited

Exploring multi-task multi-lingual learning of transformer models for hate speech and offensive speech identification in social media

Sudhanshu Mishra, Shivangi Prasad, Shubhanshu Mishra

Hate Speech has become a major content moderation issue for online social media platforms. Given the volume and velocity of online content production, it is impossible to manually…

cs.CL2020

A Framework for Generating Annotated Social Media Corpora with Demographics, Stance, Civility, and Topicality

Shubhanshu Mishra, Daniel Collier

In this paper we introduce a framework for annotating a social media text corpora for various categories. Since, social media data is generated via individuals, it is important to…

cs.CL20203 cited

Assessing Demographic Bias in Named Entity Recognition

Shubhanshu Mishra, Sijun He, Luca Belli

Named Entity Recognition (NER) is often the first step towards automated Knowledge Base (KB) generation from raw text. In this work, we assess the bias in various Named Entity Reco…