Anmol Panda
Postdoctoral Researcher, Daniels School of Business, Purdue University
anmolp [AT] purdue.edu
Bio
I am a Postdoctoral Researcher in the Management Information Systems Department at Purdue University's Daniels School of Business, where I work with Jeffrey Hu. I received my Ph.D. in Information from the University of Michigan School of Information in 2026, advised by Libby Hemphill.
I am a computational social scientist. I study how digital platforms, news organizations, and AI systems shape what information people see, what they believe, and how they take part in civic and political life. A growing part of my work asks what happens when organizations deploy AI in production: whether people trust these systems, keep using them, and are willing to pay for what they produce.
Methodologically, I combine large-scale NLP (transformer models such as BERT and RoBERTa, and LLMs) with causal inference (staggered difference-in-differences, synthetic controls) and survey and experimental designs. My research has been published in PNAS Nexus, Scientific Data, Economic & Political Weekly, and at ICWSM, CSCW, and ASIS&T.
Research
Current Research
AI, trust, and local news. How do readers respond when newsrooms use AI to produce or repackage reporting? I study the staggered rollout of AI tools across local newspapers and run experiments that vary AI-disclosure labels and content depth, measuring real behavior such as reading time and subscription choices.
Generative AI for data curation. In an IMLS-funded project with ICPSR, we use LLMs to generate variable-level metadata for social science archives at scale (about 1.9 million variables), and test which generation strategies best support data search and harmonization (ASIS&T 2026).
Politicians' social media and local businesses. This project asks whether politicians' posts that mention a business, a place, or an issue change how customers behave, using millions of Google and Yelp reviews linked to US politicians' posts from 2016 to 2021. The design separates three channels: attention, emotional appeal, and issue salience.
Past Research
Digital paywalls and civic news. Using a 17-year panel of regional US newspapers, transformer-based topic classification, and a staggered difference-in-differences design, we showed that adopting a paywall reduces local news coverage, especially in larger cities (PNAS Nexus, 2025).
Social media engagement and political behavior. My dissertation used Cooperative Election Study data from 2016 to 2024 and an original survey to study how different ways of engaging with politics on social media relate to political attitudes and support for candidates, and how these relationships differ by race, with a focus on Asian Americans.
Framing in networked publics. We studied how motivational frames spread in the #HindusUnderAttack discourse on Indian Twitter, using RoBERTa models to classify frames at scale (ICWSM 2026).
Political communication and misinformation in India. At Microsoft Research India, I co-led NivaDuck, a machine learning pipeline that identified the Twitter accounts of tens of thousands of Indian and US politicians, and used the resulting data to study election campaigns, incivility, and COVID-19 misinformation (CSCW 2020, CSCW 2021, ICTD 2020).
Publications
See all publications on
Google Scholar.
‡ indicates equal contribution.
Motivational framing in networked publics on Indian social media: A case study of #HindusUnderAttack
A. Panda, S. Z. Akbar, J. Mendelsohn, C. Budak, and M. Bui
Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 20, 1721–1737
Beyond dataset-level description: Automated keyword generation for variable discovery and harmonization in social science data
A. Panda and L. Hemphill
Proceedings of the 89th Annual Meeting of the Association for Information Science & Technology (ASIS&T), forthcoming, Nov. 2026
How digital paywalls shape news coverage
P. S. Dhillon, A. Panda, and L. Hemphill
PNAS Nexus, 4(1)
Comparative sensitivity of social media data and their acceptable use in research
L. Hemphill, A. Schöpke-Gonzalez, and A. Panda
Scientific Data, 9(1)
Misinformation as a window into prejudice: COVID-19 and the information environment in India
S. Z. Akbar, A. Panda, D. Kukreti, A. Meena, and J. Pal
CSCW 2021, ACM
NivaDuck: A scalable pipeline to build a database of political Twitter handles for India and the United States
A. Panda, A. Gonawela, S. Acharyya, D. Mishra, M. Mohapatra, R. Chandrasekaran, and J. Pal
Social Media & Society 2020
Topical focus of political campaigns and its impact: Findings from politicians’ hashtag use during the 2019 Indian elections
A. Panda, R. Kommiya Mothilal, M. Choudhury, K. Bali, and J. Pal
CSCW 2020
Motivational framing in networked publics on Indian social media: A case study of #HindusUnderAttack
A. Panda, S. Z. Akbar, J. Mendelsohn, C. Budak, and M. Bui
Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 20, 1721–1737
Beyond dataset-level description: Automated keyword generation for variable discovery and harmonization in social science data
A. Panda and L. Hemphill
Proceedings of the 89th Annual Meeting of the Association for Information Science & Technology (ASIS&T), forthcoming, Nov. 2026
How digital paywalls shape news coverage
P. S. Dhillon, A. Panda, and L. Hemphill
PNAS Nexus, 4(1)
Comparative sensitivity of social media data and their acceptable use in research
L. Hemphill, A. Schöpke-Gonzalez, and A. Panda
Scientific Data, 9(1)
Twitter in the 2019 Indian general elections: Trends of use across states and parties
J. Pal and A. Panda
Economic and Political Weekly, 54(51)
Misinformation as a window into prejudice: COVID-19 and the information environment in India
S. Z. Akbar, A. Panda, D. Kukreti, A. Meena, and J. Pal
CSCW 2021, ACM
From greetings to corruption: Politicians, political parties, and tweeting in India
L. Bozarth, A. Panda, C. Budak, and J. Pal
ICTD 2020
Affording extremes: Incivility, social media, and democracy in the Indian context
A. Panda, S. Chakraborty, N. Raval, H. Zhang, M. Mohapatra, S. Z. Akbar, and J. Pal
ICTD 2020
NivaDuck: A scalable pipeline to build a database of political Twitter handles for India and the United States
A. Panda, A. Gonawela, S. Acharyya, D. Mishra, M. Mohapatra, R. Chandrasekaran, and J. Pal
Social Media & Society 2020
Topical focus of political campaigns and its impact: Findings from politicians’ hashtag use during the 2019 Indian elections
A. Panda, R. Kommiya Mothilal, M. Choudhury, K. Bali, and J. Pal
CSCW 2020
Devotees on an astroturf: Media, politics, and outrage in the suicide of a popular filmstar
S. Z. Akbar, A. Sharma, D. Mishra, R. K. Mothilal, H. Negi, S. Nishal, A. Panda, and J. Pal
ACM COMPASS / SIGCAS 2022
Dismiss: Database of Indian social media influencers on Twitter
A. Arya, S. De, D. Mishra, G. Shekhawat, A. Sharma, A. Panda, F. Lalani, P. Singh, R. K. Mothilal, R. Grover, et al.
ICWSM 2022
Note: Picking sides—The influencer-driven #hijabban discourse on Twitter
S. De, A. Panda, and J. Pal
ACM COMPASS / SIGCAS 2022
COVID, BLM, and the polarization of US politicians on Twitter
A. Panda, D. Siddarth, and J. Pal
arXiv preprint arXiv:2008.03263
Leader or party? Personalization in Twitter political campaigns during the 2019 Indian elections
A. Rajadesingan, A. Panda, and J. Pal
Social Media & Society 2020
ConfLLVM: A compiler for enforcing data confidentiality in low-level code
A. Brahmakshatriya, P. Kedia, D. P. McKee, D. Garg, A. Lal, A. Rastogi, H. Nemati, A. Panda, and P. Bhatu
EuroSys 2019
A comparative study of GPUVerify and GKLEE
A. Panda, P. Rümmer, and N. Goveas
PDGC 2016
Political hazard: Misinformation in the 2019 Indian general election campaign
S. Z. Akbar, A. Panda, and J. Pal
In *Political Campaigning in Digital India*, Routledge
Vitæ
Full CV available as PDF .
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Purdue University 2026 – PresentPostdoctoral Researcher, Daniels School of Business
Management Information Systems Department; Advisor: Jeffrey Hu
Instructor of record, MIS 54400 Database Management Systems (Fall 2026) -
ICPSR Summer Program 2023 – 2025Teaching Assistant
Supported courses in Data Science and Text Analysis,
Data Visualization, Bayesian Models, Intermediate Mathematics, and Network Science -
The World Bank 2022Consultant, Water and Firms Team
Analyzed Enterprise Surveys data across
150+ countries using Python and Stata -
University of Michigan 2021 – 2024Graduate Student Instructor
Taught Data Mining, Deep Learning, and Python Programming
at the School of Information -
University of Michigan 2020 – 2026Ph.D., Information
Dissertation: How Media, Engagement, and Identities Relate to Political Behavior among Asian Americans
Advisor: Libby Hemphill; Committee: Joyojeet Pal, Matthew Bui, Ted Brader -
Microsoft Research India 2018 – 2020Research Fellow
Built datasets of political actors,
studied elections, extreme speech, and political communication -
Indian Institute of Technology, Delhi 2016 – 2018Senior Project Assistant
Developed compiler optimizations for packet processing pipelines with substantial throughput gains -
Uppsala University 2015 – 2016Exchange Studies
Coursework in Combinatorial Optimization,
Graph Theory, and HCI -
University of Northern British Columbia 2015Mitacs Globalink Research Intern
Developed GPS-free localization
algorithms for autonomous farm-seeding robots -
Center for Technical Education 2014 – 2015Instructor
Taught full-semester courses on Object-Oriented Programming and C# at BITS Pilani -
BITS Pilani, Goa 2012 – 2016B.E. (Hons.), Computer Science
Undergraduate Thesis: A comparative study of GPUVerify and GKLEE