“Only people who are extremely satisfied or extremely pissed off would rate the products—how to aggregate the real ratings?"—— Mitigating the Participation Bias by Balancing Extreme Ratings Yongkang Guo, Yuqing Kong, Jialiang Liu Rating aggregation plays a crucial role in various fields, such as product recommendations, hotel rankings, and teaching evaluations. However, traditional averaging methods can be affected by participation bias, where some raters do not participate in the rating process, leading to potential distortions....

My ballet class got rained out, so I ducked into a cozy café—and somehow ended up learning a bit more about Meituan and Ele.me’s business models over two cappuccinos—real coffee talk. In that café, when the barista handed the delivery guy one packed coffee. Intro: On these food delivery platforms, cafés are ranked for visibility. The higher the rank, the more orders roll in. And while it’s no surprise that paying to jump the line (read: sponsored listings) exists, what is surprising is how quietly the game is being played—not all money-boosted rankings are labeled....

Awesome paper I came across in WWW25’, using LLM to summarize a super note on top of all the community notes: Supernotes: Driving Consensus in Crowd-Sourced Fact-Checking (Courtesy to Soham’s website for the info) Soham De, Michiel A. Bakker, Jay Baxter, and Martin Saveski The ACM Web Conference. 2025 X’s Community Notes, a crowd-sourced fact-checking system, allows users to annotate potentially misleading posts. Notes rated as helpful by a diverse set of users are prominently displayed below the original post....

I watched the Australian Ballet’s 2025 season Manon at the Sydney Opera House. Mia Heathcote danced Manon tonight—she’s a soloist now, but her technique is amazing and I believe she will rise up to be principal soon. Manon’s story is unconventional for ballet where the heroine is usually, well, not a ‘slut’. The synopsis is centered around Manon, the young, beautiful but poor woman with nothing but pretty privilege, torn to choose between her love for the impoverished student Des Grieux and the allure of wealth of Monsieur G....

My advisor was busy during tea break so I was sent for the paper’s oral presentation. His loss ;) Behavior Modeling Space Reconstruction for E-Commerce Search Wang et al. WWW2025. https://doi.org/10.48550/arXiv.2501.18216 Delivering superior search services is crucial for enhancing customer experience and driving revenue growth. Conventionally, search systems model user behaviors by combining user preference and query item relevance statically, often through a fixed logical ‘and’ relationship. This paper reexamines existing approaches through a unified lens using both causal graphs and Venn diagrams, uncovering two prevalent yet significant issues: entangled preference and relevance effects, and a collapsed modeling space....

ABSOLUTELY AMAZING work: Behavioral Homophily in Social Media via Inverse Reinforcement Learning: A Reddit Case Study Yuan, Schneider and Rizoiu, WWW2025. Openreview. DOI: https://doi.org/10.1145/3696410.3714618. Arxiv. 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....

This is a reading note of an accepted oral paper at WWW2025: Welcome to the Dark Side — Analyzing the Revenue Flows of Fraud in the Online Ad Ecosystem By Emmanouil Papadogiannakis, Nicolas Kourtellis, Panagiotis Papadopoulos and Evangelos Markatos. Link: https://doi.org/10.1145/3696410.3714899 The online ad ecosystem is a mess—a densely tangled web of players with overlapping roles, and worse, a dictionary full of confusing terminologies. This paper takes a flashlight to one particularly shadowy corner (ad fraud?...

(Btw, all the WWW keynotes can be found here.) Foundation models are large, pre-trained neural network trained on broad, diverse time series data with the goal of supporting many downstream tasks (forecasting, anomaly detection, causal inference, generation) across different domains. It’s like GPT-4, but for time series analysis. 🔹 Core Capabilities of a Time Series Foundation Model: Prediction — short-term, long-term, multivariate Analysis — pattern discovery, representation learning Causal Inference — learning and modeling causal relationships over time Generation — synthetic time series for simulation or augmentation Cross-domain transfer — one model works across finance, medicine, climate, etc....

On April 21, 2025, Oh! The Federal Trade Commission filed a lawsuit today against Uber, alleging the rideshare and delivery company charged consumers for its Uber One subscription service without their consent, failed to deliver promised savings, and made it difficult for users to cancel the service despite its “cancel anytime” promises. Among the many allegations, the following may not guarantee a courtroom victory, but it stands out as the most egregious issue:...

For the paper: Price Stability and Improved Buyer Utility with Presentation Design: A Theoretical Study of the Amazon Buy Box. Ophir Friedler, Hu Fu, Anna Karlin, Ariana Tang. Accepted at The Web Conference 2025. paper pdf poster ver 1.0 Here’s the poster for WWW2025 presentation: Thanks to my advisor Hu Fu for his ideas on this.