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Web Conference Topic Selection

brycewang-stanfordbybrycewang-stanford
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Learning & Documentation

Guides research paper positioning, track selection, and venue routing for The Web Conference (WWW) and related academic conferences.

Web Conference Topic Selection provides structured decision frameworks for academic researchers targeting The Web Conference (WWW) and sibling venues like WSDM, SIGIR, KDD, and ICWSM. It applies a rigorous web-nativeness test to ensure paper relevance, matches empirical evidence to the exact reviewer expectations of all ten WWW research tracks, and assists in lane selection across full, short, Web4Good, industry, and workshop tracks. By identifying chronic submission misroutes early—such as generic ML models disguised with web datasets or interdisciplinary social papers submitted to methods tracks—it maximizes publication acceptance rates and establishes actionable plan-B submission strategies.

Key Features

01Detection and prevention of chronic submission misroutes to ML and social science venues
021,090 GitHub stars
03Evidence-based research track matching across all current WWW conference tracks
04Alternative conference routing to sibling venues including SIGIR, WSDM, KDD, and ICWSM
05Web-nativeness evaluation to distinguish core web research from swappable ML datasets
06Lane routing across full research papers, short papers, Web4Good, and Industry tracks

Use Cases

01Planning submission fallback strategies and identifying alternative conferences like SIGIR, KDD, or WSDM
02Deciding whether an AI/LLM research paper meets the web-native criteria for WWW or belongs at NeurIPS/ICLR
03Selecting the optimal reviewer track between Search, User Modeling, or Web Mining based on experimental evidence