WSDM: ACM International Conference on Web Search and Data Mining — papers and institutions, 2024–2026

Papers of WSDM, ACM International Conference on Web Search and Data Mining (CORE rank A; field: Data management and data science, Machine learning), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02. Also as Markdown.

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Key findings#

WSDM (ACM International Conference on Web Search and Data Mining) is rated A by the CORE Conference Rankings (ICORE2026); OpenAlex lists 541 of its papers from 2024–2026 (175 in 2024, 150 in 2025, 216 in 2026).
By the countries of the authors' institutions, the most papers come from China (212), the United States (189) and Australia (36).
The institutions with the most papers are Amazon (United States) (29), University of Science and Technology of China (24) and Chinese Academy of Sciences (17).
Its most-cited paper of these years is “LLMRec: Large Language Models with Graph Augmentation for Recommendation” (2024), with 284 citations.

Papers per year#

WSDM papers per publication year in OpenAlex (–: not in OpenAlex yet)
Year	Papers	With affiliations
2024	175	164
2025	150	144
2026	216	210

Sources#

Where OpenAlex lists the papers
OpenAlex source	Which papers
S4363608885	The conference's proceedings

Who publishes there#

Institutions with the most WSDM papers, 2024–2026
#	Institution	Papers
1	Amazon (United States)	29
2	University of Science and Technology of China	24
3	Chinese Academy of Sciences	17
4	Alibaba Group (China)	17
5	University of Chinese Academy of Sciences	15
6	Tsinghua University	15
7	Google (United States)	14
8	Tencent (China)	14
9	Ant Group (China)	14
10	Beihang University	14

Countries with the most WSDM papers, 2024–2026
#	Country	Papers
1	China	212
2	United States	189
3	Australia	36
4	South Korea	33
5	Hong Kong	31
6	Germany	27
7	Singapore	25
8	United Kingdom	20
9	Canada	19
10	Netherlands	16

Keywords with the most WSDM papers, 2024–2026
#	Keyword	Papers
1	large language models	101
2	graph neural networks	53
3	recommender systems	50
4	sequential recommendation	23
5	contrastive learning	17
6	knowledge graphs	17
7	retrieval-augmented generation	16
8	node classification	15
9	personalized recommendation	15
10	causal inference	14

Most-cited papers#

Most-cited WSDM papers of 2024–2026 (citations counted by OpenAlex)
#	Citations	Title	Published	Authors
1	284	LLMRec: Large Language Models with Graph Augmentation for Recommendation	2024-03-04	Wei Wei, Xubin Ren, Jiabin Tang et al.
2	161	DiffKG: Knowledge Graph Diffusion Model for Recommendation	2024-03-04	Yangqin Jiang, Yuhao Yang, Lianghao Xia et al.
3	155	Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study	2024-03-04	Yuan Sui, Mengyu Zhou, Mingjie Zhou et al.
4	124	ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models	2024-03-04	Qijiong Liu, Nuo Chen, Tetsuya Sakai et al.
5	108	GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction	2024-03-04	Amit Roy, Juan Shu, Jia Li et al.
6	96	Linear Recurrent Units for Sequential Recommendation	2024-03-04	Zhenrui Yue, Y. Wang, Zhankui He et al.
7	88	K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization	2024-03-04	Cheng Deng, Tianhang Zhang, Zhongmou He et al.
8	73	Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation	2024-03-04	Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao et al.
9	72	Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM Interactions	2024-03-04	Zahra Abbasiantaeb, Yifei Yuan, Evangelos Kanoulas et al.
10	70	HealAI: A Healthcare LLM for Effective Medical Documentation	2024-03-04	Sagar Goyal, Eti Rastogi, Sree Prasanna Rajagopal et al.

Conferences in the same field#

AAAI · NeurIPS · IJCAI · KDD · WWW · SIGIR · VLDB · ICDE · SIGMOD · ICDM · PODS · CIKM · ECAI · ECML PKDD · RecSys · ECIR · ICWSM · ICDAR · MSR · SIGSPATIAL · PPSN · ISWC · SDM · CAiSE · ICDT · ER

Cite this page

Scholar4AI. (2026). WSDM: ACM International Conference on Web Search and Data Mining — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/wsdm

@misc{scholar4ai-proceedings-wsdm,
  author = {{Scholar4AI}},
  title = {WSDM: ACM International Conference on Web Search and Data Mining — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/wsdm}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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