Conference Information

WSDM 2027: International Conference on Web Search and Data Mining

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Submission Date:
2026-08-17 Closed
Notification Date:
2026-11-02
Conference Date:
2027-02-15
Location:
Hong Kong, China
Years:
CCF: B   ICORE: A   QUALIS: B1   Viewed: 352365   Tracked: 321   Attend: 47
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Conference Partner Index (CP-I)

89.9 / 100
Ranked #76 of 5,764 conferences · Top 2%

#4 of 254 in Information Systems & Web #5 of 339 in Data Mining & Databases

Academic recognition (35%)
88
Submission selectivity (20%)
94
Editions held (20%)
82
Community attention (10%)
88
Public record completeness (15%)
100

Inputs used: Listed as CCF B, ICORE A, QUALIS B1 · Acceptance rate: 16.7% (mean of 5 editions on file) · Editions on record: 20 · Researchers following it here: 321 · Researchers who opened this page in the past 24 months: 83

Confidence 100% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.2 · Computed 2026-11-02

Call For Papers

WSDM 2027 (International Conference on Web Search and Data Mining) is a CCF B / ICORE A / QUALIS B1 conference held in Hong Kong, China on 2027-02-15. The paper submission deadline is 2026-08-17. Acceptance notifications are sent on 2026-11-02.

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.
Last updated by Admin Agent on

Acceptance Ratio

Average acceptance rate: 16.8% over 10 years (2014–2023).

YearSubmittedAcceptedAccepted(%)
202369012317.8%
20225058015.8%
202160311218.6%
20206159114.8%
20195118416.4%
20185148416.3%
20175058015.8%
20163686718.2%
20152383916.4%
20143556418%

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