--- title: "Top Marketing conferences (CORE A*/A) 2024–2026" description: "3 conferences rated A* or A by the CORE ICORE2026 ranking are listed for Marketing; OpenAlex lists 1,799 papers from 2024–2026 for them. The largest are RecSys (740), WSDM (541) and ICWSM (518)." url: https://scholar4ai.com/proceedings/categories/marketing markdown_url: https://scholar4ai.com/proceedings/categories/marketing.md license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/) share_text: "3 conferences rated A* or A by the CORE ICORE2026 ranking are listed for Marketing; OpenAlex lists 1,799 papers from 2024–2026 for them. The largest are RecSys (740), WSDM (541) and ICWSM (518). (as of 2026-11-02)" data_url: https://scholar4ai.com/data/rankings.json updated: 2026-11-02T12:20:52+09:00 window: 2026-10-04 to 2026-11-02 source: OpenAlex (CC0) --- # Marketing conference proceedings: CORE A* and A conferences, 2024–2026 The conferences rated A* or A by the CORE Conference Rankings (ICORE2026) that relate to marketing: RecSys, ICWSM and WSDM. A conference can be listed under several categories. 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. All conferences: https://scholar4ai.com/proceedings.md · Marketing journals dashboard: https://scholar4ai.com/categories/marketing.md ## Key findings - 3 conferences rated A* or A by the CORE ICORE2026 ranking are listed for Marketing; OpenAlex lists 1,799 papers from 2024–2026 for them. - The largest are RecSys (740), WSDM (541) and ICWSM (518). - The most-cited paper is “LLMRec: Large Language Models with Graph Augmentation for Recommendation” (WSDM, 2024), with 284 citations. ## Conferences *CORE A* and A conferences for Marketing: papers per publication year, 2024–2026 (–: not in OpenAlex yet)* | Conference | Name | Rank | Field | 2024 | 2025 | 2026 | 2024–2026 | |---|---|---|---|---:|---:|---:|---:| | [RecSys](https://scholar4ai.com/proceedings/recsys.md) | ACM International Conference on Recommender Systems | A | Data management and data science | 217 | 239 | 284 | 740 | | [WSDM](https://scholar4ai.com/proceedings/wsdm.md) | ACM International Conference on Web Search and Data Mining | A | Data management and data science, Machine learning | 175 | 150 | 216 | 541 | | [ICWSM](https://scholar4ai.com/proceedings/icwsm.md) | International Conference on Web and Social Media | A | Applied computing, Data management and data science | 162 | 170 | 186 | 518 | ## Most-cited papers *Most-cited papers of these conferences, 2024–2026 (citations counted by OpenAlex)* | # | Citations | Title | Conference | Published | |---:|---:|---|---|---| | 1 | 284 | [LLMRec: Large Language Models with Graph Augmentation for Recommendation](https://doi.org/10.1145/3616855.3635853) | WSDM | 2024-03-04 | | 2 | 161 | [DiffKG: Knowledge Graph Diffusion Model for Recommendation](https://doi.org/10.1145/3616855.3635850) | WSDM | 2024-03-04 | | 3 | 156 | [Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models](https://doi.org/10.1145/3640457.3688104) | RecSys | 2024-10-08 | | 4 | 155 | [Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study](https://doi.org/10.1145/3616855.3635752) | WSDM | 2024-03-04 | | 5 | 124 | [ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models](https://doi.org/10.1145/3616855.3635845) | WSDM | 2024-03-04 | | 6 | 108 | [GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction](https://doi.org/10.1145/3616855.3635767) | WSDM | 2024-03-04 | | 7 | 96 | [Linear Recurrent Units for Sequential Recommendation](https://doi.org/10.1145/3616855.3635760) | WSDM | 2024-03-04 | | 8 | 88 | [K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization](https://doi.org/10.1145/3616855.3635772) | WSDM | 2024-03-04 | | 9 | 73 | [Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation](https://doi.org/10.1145/3616855.3635773) | WSDM | 2024-03-04 | | 10 | 72 | [Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM Interactions](https://doi.org/10.1145/3616855.3635856) | WSDM | 2024-03-04 | ## Cite this page Scholar4AI. (2026). Marketing conference proceedings: CORE A* and A conferences, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/categories/marketing ```bibtex @misc{scholar4ai-proceedings-categories-marketing, author = {{Scholar4AI}}, title = {Marketing conference proceedings: CORE A* and A conferences, 2024–2026}, year = {2026}, howpublished = {\url{https://scholar4ai.com/proceedings/categories/marketing}}, urldate = {2026-11-02}, note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0} } ``` License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).