WSDM (pronounced “wisdom”) is one of the premier conferences on web-inspired research involving search and data mining. WSDM is a highly selective conference that includes invited talks, as well as refereed full papers. WSDM publishes original, high-quality papers related to search and data mining on the Web and the Social Web, with an emphasis on practical yet principled novel models of search and data mining, algorithm design and analysis, economic implications, and in-depth experimental analysis of accuracy and performance.

List of Topics

Papers accepted to WSDM will be published in the ACM Digital Library. We invite submissions on a broad range of topics related to search and data mining on the Web and Social Web. Areas of interest include, but are not limited to, the following topics:

Web Search
Algorithms for web-scale search; Adversarial search; Search user interfaces and interaction; Distributed search, metasearch, peer-to-peer search; Local and mobile search; Multimedia web search, cross-lingual search; Query analysis and query processing; Search benchmarking and evaluation; Search user behavior and log analysis.

Web Mining and Content Analysis
Crawling and indexing web content; Web recommender systems and algorithms; Agentic recommender systems; Clustering, classification, and summarization of web data; Data, entity, event, and relationship extraction; Knowledge acquisition and automatic construction of knowledge bases; Large-scale graph analysis; Semantic search, faceted search, and knowledge graphs; Scalable algorithms for mining web data; Opinion mining and sentiment analysis; Web traffic and log analysis; Web measurements, web evolution, and web models; Generative web applications;

Foundation Models and Agentic Systems
LLMs and multimodal foundation models for web tasks; Generative question answering and reasoning; Retrieval, indexing, and ranking with foundation models; Evaluation and benchmarking of foundation models in search/mining; Web agents; GUI agents/multi-agent systems in Web search, recommendation, and interactive information retrieval; Continual learning and self-evolution; Memory systems of foundation models; User interfaces and experiences powered by foundation models.

Web of Things, Ubiquitous and Mobile Computing
Geo-location data analysis; Mobility and behavior data mining; Location-based social networks; User activity modeling and exploitation.

Privacy, Fairness, Interpretability
Fairness and accountability in ranking, recommendations and advertising; Explainability in web systems; Model and algorithm transparency; Web search and data mining under privacy constraints; Fairness and interpretability in applications of web mining for social good.

Social Networks
Link prediction and community detection; Social network analysis and graph algorithms; Computational social science; Influence and viral marketing in social networks; Social sensing; Searching social and real-time content; Social network dynamics; Sampling, experiments, and evaluation in social networks; Social media analysis: blogs and friendship networks; Social network analysis, theories, models and applications; Social reputation and trust.

Intelligent Assistants
Voice search, conversational search, and dialog systems; Personal assistants, dialogue models, and conversational interaction; Task-driven search; Zero-query and implicit search.

Crowdsourcing and Human Computation
Collaborative search and question answering; Human-in-the-Loop and Collaborative Human-AI systems.

Information Integrity
Systems and algorithms for monitoring and detection of misinformation and fake news; Prevalence and virality of misinformation; Misinformation sources and origins; Source and content credibility; Detecting and combating spamming, trolling, aggression, dog whistles, and toxic online behaviors; Methods for detecting and mitigating low quality and offensive content, bullying and hate speech, and coordinated behavior; Polarization, extremism and radicalization; Echo chambers and filter bubbles.

Emerging and Creative Applications
Systems and algorithms for urban applications such as smart cities/digital twins; Climate, sustainability, and environmental intelligence systems; Online education systems; Monitoring and prevention of epidemics; Healthcare and clinical decision support; Embodied AI systems interacting with web and real-world environments; AI for Data-rich Science; Scientific Foundation Models.