papers

Publications (11)

cs.CL2017

Automatic Identification of Sarcasm Target: An Introductory Approach

Aditya Joshi, Pranav Goel, Pushpak Bhattacharyya +1

Past work in computational sarcasm deals primarily with sarcasm detection. In this paper, we introduce a novel, related problem: sarcasm target identification i.e., extracting the…

cs.SI2025

DomainDemo: a dataset of domain-sharing activities among different demographic groups on Twitter

Kai-Cheng Yang, Pranav Goel, Alexi Quintana-Mathé +5

Social media play a pivotal role in disseminating web content, particularly during elections, yet our understanding of the association between demographic factors and information s…

cs.CL2022

Are Neural Topic Models Broken?

Alexander Hoyle, Pranav Goel, Rupak Sarkar +1

Recently, the relationship between automated and human evaluation of topic models has been called into question. Method developers have staked the efficacy of new topic model varia…

cs.CL2020

Towards Automatic Generation of Questions from Long Answers

Shlok Kumar Mishra, Pranav Goel, Abhishek Sharma +3

Automatic question generation (AQG) has broad applicability in domains such as tutoring systems, conversational agents, healthcare literacy, and information retrieval. Existing eff…

cs.CL2020

Improving Neural Topic Models using Knowledge Distillation

Alexander Hoyle, Pranav Goel, Philip Resnik

Topic models are often used to identify human-interpretable topics to help make sense of large document collections. We use knowledge distillation to combine the best attributes of…

cs.SI2025

Using co-sharing to identify use of mainstream news for promoting potentially misleading narratives

Pranav Goel, Jon Green, David Lazer +1

Much of the research quantifying volume and spread of online misinformation measures the construct at the source level, identifying a set of specific unreliable domains that accoun…

cs.CL2024

Improving the TENOR of Labeling: Re-evaluating Topic Models for Content Analysis

Zongxia Li, Andrew Mao, Daniel Stephens +5

Topic models are a popular tool for understanding text collections, but their evaluation has been a point of contention. Automated evaluation metrics such as coherence are often us…

cs.CL2025

Measuring Scalar Constructs in Social Science with LLMs

Hauke Licht, Rupak Sarkar, Patrick Y. Wu +4

Many constructs that characterize language, like its complexity or emotionality, have a naturally continuous semantic structure; a public speech is not just "simple" or "complex,"…

cs.CL2025

Natural Language Decompositions of Implicit Content Enable Better Text Representations

Alexander Hoyle, Rupak Sarkar, Pranav Goel +1

When people interpret text, they rely on inferences that go beyond the observed language itself. Inspired by this observation, we introduce a method for the analysis of text that t…

cs.CL2021

Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence

Alexander Hoyle, Pranav Goel, Denis Peskov +3

Topic model evaluation, like evaluation of other unsupervised methods, can be contentious. However, the field has coalesced around automated estimates of topic coherence, which rel…

cs.CL2021

Studying word order through iterative shuffling

Nikolay Malkin, Sameera Lanka, Pranav Goel +1

As neural language models approach human performance on NLP benchmark tasks, their advances are widely seen as evidence of an increasingly complex understanding of syntax. This vie…