9 citations · 47 across the 16 of their papers we have counts for
7 papers · 1 filter
The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis
Pranav Narayanan Venkit, Mukund Srinath, Sanjana Gautam +4
We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets. Our i…
Towards a Holistic Approach: Understanding Sociodemographic Biases in NLP Models using an Interdisciplinary Lens
Pranav Narayanan Venkit
The rapid growth in the usage and applications of Natural Language Processing (NLP) in various sociotechnical solutions has highlighted the need for a comprehensive understanding o…
Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles
Pranav Narayanan Venkit, Sanjana Gautam, Ruchi Panchanadikar +2
We investigate the potential for nationality biases in natural language processing (NLP) models using human evaluation methods. Biased NLP models can perpetuate stereotypes and lea…
CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Bias
Vipul Gupta, Pranav Narayanan Venkit, Hugo Laurençon +2
As language models (LMs) become increasingly powerful and widely used, it is important to quantify them for sociodemographic bias with potential for harm. Prior measures of bias ar…
Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models
Pranav Narayanan Venkit, Mukund Srinath, Shomir Wilson
We analyze sentiment analysis and toxicity detection models to detect the presence of explicit bias against people with disability (PWD). We employ the bias identification framewor…
Sociodemographic Bias in Language Models: A Survey and Forward Path
Vipul Gupta, Pranav Narayanan Venkit, Shomir Wilson +1
Sociodemographic bias in language models (LMs) has the potential for harm when deployed in real-world settings. This paper presents a comprehensive survey of the past decade of res…
Nationality Bias in Text Generation
Pranav Narayanan Venkit, Sanjana Gautam, Ruchi Panchanadikar +2
Little attention is placed on analyzing nationality bias in language models, especially when nationality is highly used as a factor in increasing the performance of social NLP mode…