WSDM (pronounced “wisdom”) is one of the premier conferences on web-inspired research involving search and data mining. The 16th ACM International WSDM Conference will take place in Singapore (in-person conference with virtual elements), from February 27 to March 3, 2023.
WSDM is a highly selective conference that includes refereed full papers as well as invited talks. 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 approaches.
Original papers emphasizing novel algorithmic approaches are particularly encouraged. Application-oriented papers that make innovative technical contributions to research are welcome. Visionary papers on new and emerging topics are particularly encouraged.
Authors are explicitly discouraged from submitting papers that do not clearly present their contribution with respect to previous works, that contain only incremental results, and that do not provide significant advances over existing approaches.
Important Dates
| Papers Due | August 12, 2022 |
| Notifications | October 21, 2022 |
| Camera-ready | December 19, 2022 |
| Conference | February 27, 2023 - March 3, 2023 |
All deadlines are 11:59pm, anywhere on earth.
List of Topics
WSDM proceedings are published in the ACM Digital Library. We invite papers in the areas below, with example topics listed for each area.
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, crosslingual search; Query analysis and query processing; Search benchmarking and evaluation; Search user behavior and log analysis; Search with Foundation Models
Web Mining and Content Analysis
Crawling and indexing web content; Web recommender systems and algorithms; 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; Multimodal data mining; Scalable algorithms for mining web data; Opinion mining and sentiment analysis; Web traffic and log analysis; Web measurements, web evolution, and web 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; Interpretable models of individual and social behavior; Web search and data mining under privacy constraints.
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.
Emerging Applications
Monitoring and prevention of epidemics; Mental health and well-being support systems; Systems and algorithms for urban applications; Online education systems; Web Mining for Social Good.
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, and toxic online behaviors; Methods for detecting and mitigating low quality and offensive content, bullying and hate speech; Polarization, Extremism and Radicalization; Echo chambers and Filter bubbles.
Submission Guidelines
Link for Submissions
Papers can be submitted through CMT: https://cmt3.research.microsoft.com/WSDM2023
Originality of Submissions
Submissions must represent new and original work. Concurrent submissions are not allowed. Papers that have been published in or accepted to any peer-reviewed journal or conference or workshop with published proceedings, or that are currently under review, or that will be submitted to other meetings or publications while under review, may not be submitted to WSDM 2023. However, submissions that are available online (e.g., on a preprint server such as Arxiv) and/or have been previously presented orally or as posters in non peer-reviewed venues with no formal proceedings, are allowed. Additionally, the ACM has a strict policy against plagiarism and self-plagiarism. All prior work must be appropriately cited.
Format of Submissions
Papers must be submitted in PDF according to the new ACM format published in ACM guidelines, selecting the generic “sigconf” sample. Submissions should not exceed eight pages including any diagrams or tables, plus up to one additional page of references. The PDF files must have all non-standard fonts embedded. Submissions must be self-contained and in English. After uploading your submission, please verify the copy stored on the CMT site. Submissions that do not follow these guidelines, or do not view or print properly, may be rejected without review.
PDF files submitted to WSDM 2023 must be double-blind: the submitted document should not include the author information and should not include citations or discussion of related work that would make the authorship apparent. Explicitly revealing the paper authorship will result in rejection without review. Note, however, that it is acceptable to explicitly refer in the paper to companies or organizations that provided datasets, hosted experiments, or deployed solutions. To this end, instead of stating, for instance, that an experiment “was conducted on the logs of a major search engine”, the authors should refer to the search engine by name. The reviewers will be informed that it does not necessarily imply that the authors are currently affiliated with the mentioned organization. To support the identification of reviewers with conflicts of interest, the full author list must be specified at submission time. To support the rapid dissemination of scientific results, we allow submissions that had earlier versions or code posted on preprint servers such as Arxiv.org or GitHub (with the understanding that these materials cannot be considered double-blind). In such cases, authors should exercise extra care and should not explicitly associate their submission with such publicly posted materials.
Authorship
We believe that the listed authors should have significant involvement with each paper bearing their name. If one submits numerous papers to the same conference, it is less likely that one has materially contributed to all such submissions. To this end, we limit the number of submissions per author to 10 maximum. If more than 10 papers are submitted with the same person listed as an author, the additional papers submitted after the initial 10, will be rejected without review.
Only in exceptional cases will the PC Chairs grant permission for modifications to be made to the author list of a paper once it has been submitted and accepted.
Review Process
Each paper will be reviewed by at least three PC members and a senior PC member. The acceptance decisions will take into account paper novelty, technical depth, elegance, practical or theoretical impact, and presentation. WSDM 2023 will use a combination of single-blind reviewing and double-blind reviewing. The papers will be double-blind to regular PC members, but the metadata (including authorship) of the papers will be available to SPC to check for undisclosed conflicts of interest and to help assure the integrity of the review process.
Reproducibility
The algorithms, resources and methods used within a paper should be described as completely as possible. Authors may reference supplementary material, including detailed descriptions, test datasets or code external repositories with datasets or code, but should only do so if strict author anonymity can be maintained. These external repositories may also contain a PDF with extended proofs, if these are important for reproducing theoretical results in the paper. The additional content may or may not be considered when evaluating the paper, at the discretion of the reviewers. Wherever appropriate, the authors are encouraged to use publicly available test collections and state-of-the-art baselines, and are encouraged to share the experimental results, data, and code with the research community.
ACM Instructions for Authors
By submitting your article to an ACM Publication, you are hereby acknowledging that you and your co-authors are subject to all ACM Publications Policies, including ACM's new Publications Policy on Research Involving Human Participants and Subjects. Alleged violations of this policy or any ACM Publications Policy will be investigated by ACM and may result in a full retraction of your paper, in addition to other potential penalties, as per ACM Publications Policy.
Please ensure that you and your co-authors obtain an ORCID ID, so you can complete the publishing process for your accepted paper. ACM has been involved in ORCID from the start and we have recently made a commitment to collect ORCID IDs from all of our published authors. The collection process has started and will roll out as a requirement throughout 2022. We are committed to improve author discoverability, ensure proper attribution and contribute to ongoing community efforts around name normalization; your ORCID ID will help in these efforts.
Best Papers from WSDM 2023
The 10 best papers considered by The WSDM 2023 Best Paper Award Committee will be considered to be published in TIST (ACM Transactions on Intelligent Systems). The guest editors consist of the best paper award committee chair and the 3 PC chairs.
Conflict of Interest (COI) Policy
All authors and reviewers must declare conflicts of interest in CMT.
You must declare a reviewer/author as a conflict of interest when the following associations exist:
-
employment at the same institution or company, regardless of geography/location, currently or in the last 12 months
-
candidate for employment at the same institution or company
-
received an honorarium, stipend, or grant from the institution or company within the last 12 months (except where of a modest nature, such as reimbursement of seminar expenses, honorarium for examination of a thesis, and so on).
-
co-author on book or paper in the last 24 months
-
co-principal investigator on a funded grant or research proposal in the last 24 months
-
actively working on any project together
-
family relationship or close personal relationship
-
graduate advisee/advisor relationship, regardless of time elapsed since graduation
-
deep personal animosity
In general, we expect authors, PC, the organizing committee, and other volunteers to adhere to ACM’s Conflict of Interest Policy as well as the ACM’s Code of Ethics and Professional Conduct.
Violations of Originality, Dual Submission or Conflicts of Interest
Submitted papers that do not meet the length, formatting or originality requirements, or are dually submitted to two venues (including papers with significant overlap), are subject to desk rejection without review. At the discretion of the PC Chairs and the Steering Committee, egregious violations (including plagiarism) may lead to additional penalties such as a temporary or permanent ban from the venue and sponsoring SIGs venues. Likewise, failure of an author to disclose all COIs, or cases of a referee providing a review on a paper for which they have an undisclosed COI, may lead to similar penalties. You are encouraged to contact the PC Chairs if you have questions as to the originality conditions, dual submission, or conflict of interest policy.
