---
title: "WWW (A*): papers and universities"
description: "WWW (International World Wide Web Conference) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 2,725 of its papers from 2024–2026 (786 in 2024, 979 in 2025, 960 in 2026). By the countries of the authors' institutions, the most papers come from China (1,469), the United States (647) and Australia (349)."
url: https://scholar4ai.com/proceedings/www
markdown_url: https://scholar4ai.com/proceedings/www.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "WWW (International World Wide Web Conference) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 2,725 of its papers from 2024–2026 (786 in 2024, 979 in 2025, 960 in 2026). (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)
---

# WWW: International World Wide Web Conference — papers and institutions, 2024–2026

Papers of WWW, International World Wide Web Conference (CORE rank A*; field: Distributed computing and systems software, Data management and data science), 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.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- WWW (International World Wide Web Conference) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 2,725 of its papers from 2024–2026 (786 in 2024, 979 in 2025, 960 in 2026).
- By the countries of the authors' institutions, the most papers come from China (1,469), the United States (647) and Australia (349).
- The institutions with the most papers are Zhejiang University (131), Tsinghua University (130) and University of Science and Technology of China (113).
- Its most-cited paper of these years is “Representation Learning with Large Language Models for Recommendation” (2024), with 244 citations.

## Papers per year

*WWW papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 786 | 776 |
| 2025 | 979 | 964 |
| 2026 | 960 | 946 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S7407088480](https://openalex.org/S7407088480) | The conference's proceedings |

## Who publishes there

*Institutions with the most WWW papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 131 |
| 2 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 130 |
| 3 | [University of Science and Technology of China](https://scholar4ai.com/institutions/university-of-science-and-technology-of-china.md) | 113 |
| 4 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 109 |
| 5 | [National University of Singapore](https://scholar4ai.com/institutions/national-university-of-singapore.md) | 86 |
| 6 | [University of Chinese Academy of Sciences](https://scholar4ai.com/institutions/university-of-chinese-academy-of-sciences.md) | 74 |
| 7 | [Renmin University of China](https://scholar4ai.com/institutions/renmin-university-of-china.md) | 73 |
| 8 | [Peking University](https://scholar4ai.com/institutions/peking-university.md) | 72 |
| 9 | The Hong Kong University of Science and Technology (Guangzhou) | 72 |
| 10 | Alibaba Group (China) | 69 |

*Countries with the most WWW papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 1,469 |
| 2 | United States | 647 |
| 3 | Australia | 349 |
| 4 | Singapore | 200 |
| 5 | Hong Kong | 193 |
| 6 | United Kingdom | 142 |
| 7 | Germany | 104 |
| 8 | South Korea | 104 |
| 9 | Canada | 63 |
| 10 | India | 62 |

*Keywords with the most WWW papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 584 |
| 2 | [graph neural networks](https://scholar4ai.com/keywords/graph-neural-networks.md) | 192 |
| 3 | recommender systems | 174 |
| 4 | retrieval-augmented generation | 100 |
| 5 | [contrastive learning](https://scholar4ai.com/keywords/contrastive-learning.md) | 77 |
| 6 | [federated learning](https://scholar4ai.com/keywords/federated-learning.md) | 60 |
| 7 | social media | 59 |
| 8 | knowledge graphs | 54 |
| 9 | personalized recommendation | 46 |
| 10 | diffusion models | 45 |

## Most-cited papers

*Most-cited WWW papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 244 | [Representation Learning with Large Language Models for Recommendation](https://doi.org/10.1145/3589334.3645458) | 2024-05-08 | Xubin Ren, Wei Wei, Lianghao Xia et al. |
| 2 | 176 | [A Multifaceted Look at Starlink Performance](https://doi.org/10.1145/3589334.3645328) | 2024-05-08 | Nitinder Mohan, Andrew E. Ferguson, Hendrik L. Cech et al. |
| 3 | 176 | [MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models](https://doi.org/10.1145/3589334.3648137) | 2024-05-08 | Kailai Yang, Tianlin Zhang, Ziyan Kuang et al. |
| 4 | 144 | [Is Cosine-Similarity of Embeddings Really About Similarity?](https://doi.org/10.1145/3589335.3651526) | 2024-05-12 | Harald Steck, Chaitanya Ekanadham, Nathan Kallus |
| 5 | 118 | [MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilot](https://doi.org/10.1145/3696410.3714782) | 2025-04-22 | Xuejiao Zhao, Siyan Liu, Su-Yin Yang et al. |
| 6 | 115 | [UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting](https://doi.org/10.1145/3589334.3645434) | 2024-05-08 | Xu Liu, Junfeng Hu, Yuan Li et al. |
| 7 | 107 | [Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective](https://doi.org/10.1145/3589334.3645710) | 2024-05-08 | Zexin Wang, Changhua Pei, Minghua Ma et al. |
| 8 | 107 | [Collaborative Large Language Model for Recommender Systems](https://doi.org/10.1145/3589334.3645347) | 2024-05-08 | Yaochen Zhu, Liang Wu, Qi Sheng Guo et al. |
| 9 | 94 | [AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems](https://doi.org/10.1145/3589334.3645537) | 2024-05-08 | Junjie Zhang, Yupeng Hou, Ruobing Xie et al. |
| 10 | 81 | [Better to Ask in English: Cross-Lingual Evaluation of Large Language Models for Healthcare Queries](https://doi.org/10.1145/3589334.3645643) | 2024-05-08 | Yiqiao Jin, Mohit Chandra, Gaurav Verma et al. |

## Cite this page

Scholar4AI. (2026). WWW: International World Wide Web Conference — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/www

```bibtex
@misc{scholar4ai-proceedings-www,
  author = {{Scholar4AI}},
  title = {WWW: International World Wide Web Conference — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/www}},
  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/).