Philipp Schneider wins 2025 Web Conference Best Paper Award

Philipp Schneider with Lanqin Yuan and Marian-Andrei Rizoiu© 2025 EPFL

Philipp Schneider with Lanqin Yuan and Marian-Andrei Rizoiu© 2025 EPFL

Philipp Schneider won the Best Paper Award at the 2025 ACM Web Conference (WWW '25) for his paper "Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Study" (co-authored with Lanqin Yuan and Marian-Andrei Rizoiu - both University of Technology Sydney).

The Web Conference (formerly WWW conference) is a yearly international conference on the topic of the future directions of the World Wide Web.

The Conference aims to provide the world with a premier forum for discussion and debate about the evolution of the Web, the standardization of its associated technologies, and the impact of those technologies on society and culture. The conference brings together researchers, developers, users and commercial ventures — indeed all those who are passionate about the Web and what it has to offer.

Abstract:

Online communities play a critical role in shaping societal discourse and influencing collective behavior in the real world. The tendency for people to connect with others who share similar characteristics and views, known as homophily, plays a key role in the formation of echo chambers which further amplify polarization and division. Existing works examining homophily in online communities traditionally infer it using

content- or adjacency-based approaches, such as constructing explicit interaction networks or performing topic analysis. These methods fall short for platforms where interaction networks cannot be easily constructed and fail to capture the complex nature of user interactions across the platform. This work introduces a novel approach for quantifying user homophily. We first use an Inverse Reinforcement Learning (IRL) framework to infer users' policies, then use these policies as a measure of behavioral homophily. We apply our method to Reddit, conducting a case study across 5.9 million interactions over six years, demonstrating how this approach uncovers distinct behavioral patterns and user roles that vary across different communities. We further validate our behavioral homophily measure against traditional content-based homophily, offering a powerful method for analyzing social media dynamics and their broader societal implications. We find, among others, that users can behave very similarly (high behavioral homophily) when discussing entirely different topics like soccer vs e-sports (low topical homophily), and that there is an entire class of users on Reddit whose purpose seems to be to disagree with others.