Juhi Kulshrestha

Dr. Juhi Kulshrestha

Assistant Professor, Aalto University

Juhi Kulshrestha is a computational social scientist whose research lies at the intersection of computer science, data science, and social systems. She is especially interested in topics such as algorithmic bias, online political discourse, digital inequalities, and platform accountability. Her work often leverages large-scale digital trace data, experimental methods, and web tracking.

Research Interests: Computational Social Science, Misinformation, Algorithmic Audits, Political Communication, Digital Trace Data

Google Scholar Personal Website

Selected Recent Publications
Characteristics of ChatGPT users from Germany: Implications for the digital divide from web tracking data
PLoS ONE, 2025

Authors: Celina Kacperski, Roberto Ulloa, Denis Bonnay, Juhi Kulshrestha, Peter Selb, Andreas Spitz

This study analyzes how user characteristics predict the use of ChatGPT in Germany. Using a combination of behavioral web-tracking and survey data from 1,376 citizens, the authors show that age, education, employment status, and political engagement shape AI usage. The findings reveal digital divides along socio-political dimensions, with implications for technology adoption and digital literacy.

View full paper on PLOS ONE
Sleep During the COVID-19 Pandemic: Longitudinal Observational Study Combining Multisensor Data With Questionnaires
JMIR Mhealth Uhealth, 2024

Authors: Nguyen Luong, Gloria Mark, Juhi Kulshrestha, Talayeh Aledavood

This study examines sleep patterns of working adults during the late stage of the COVID-19 pandemic using a combination of wearable sensor data and monthly questionnaires over a year in Finland. It explores the impact of five sets of variables — demographics, sleep-related habits, physical activity, pandemic-specific constraints, and seasonal variations — on sleep. Findings show that stricter pandemic measures led to longer total sleep time and later midsleep. Physical activity timing, job type, and circadian rhythm variability also played significant roles. The study offers a comprehensive view on how lifestyle and policy changes influenced sleep during a time of societal shift.

View full paper on JMIR Mhealth Uhealth
Novelty in News Search: A Longitudinal Study of the 2020 US Elections
Published 2023

Authors: Roberto Ulloa, Mykola Makhortykh, Aleksandra Urman, Juhi Kulshrestha

This study investigates how search engines handle fast-evolving news content during high-intensity events, such as the 2020 US presidential elections. By simulating human browsing and collecting news search results every 21 minutes from two global locations, the researchers examine the appearance of "novel" news items — newly emerging results — across different search engines. Findings reveal significant differences in how often and what type of news content appeared depending on the query topic and the engine used. Notably, candidate-related searches showed imbalance in novelty, potentially influencing public visibility and perceptions. The study sheds light on how algorithmic and editorial choices shape political information exposure online.

View full paper on Social Science Computer Review

More publications on Google Scholar →