Social Algorithm Team at Tencent

We are a group of researchers and engineers, whose interests are to develop effective and efficient algorithms and models to optimize and analyze the experience of users in practical social networks. Our technologies have been deployed in various application scenarios of several products at Tencent Games serving a massive number of active users.

We are looking for self-motivated interns or team members. Please send edwlin@tencent.com your resume if interested.

Selected Publications @ Tencent
Marked with ˚ are interns, and ° are team members.

SIGKDD 2024          



Beyond Binary Preference: Leveraging Bayesian Approaches for Joint Optimization of Ranking and Calibration. [code]
Chang Liu˚, Qiwei Wang°, Wenqing Lin°, Yue Ding, Hongtao Lu.
Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 5442 - 5453, 2024.

SIGKDD 2024          



DAG: Deep Adaptive and Generative K-Free Community Detection on Attributed Graphs.
Chang Liu˚, Yuwen Yang, Yue Ding, Hongtao Lu, Wenqing Lin°, Ziming Wu°, Wendong Bi°.
Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 5454 - 5465, 2024.

WWW 2024          



Information Diffusion Meets Invitation Mechanism. [code, video]
Shiqi Zhang˚, Jiachen Sun°, Wenqing Lin°, Xiaokui Xiao, Yiqian Huang, Bo Tang.
Proceedings of the ACM Web Conference (WWW), pages 383-392, 2024.

PVLDB 2024          



Minimum Strongly Connected Subgraph Collection in Dynamic Graphs. [code]
Xin Chen˚, Jieming Shi, You Peng, Wenqing Lin°, Sibo Wang, Wenjie Zhang.
Proceedings of the VLDB Endowment (PVLDB), 17(6): 1324-1336, 2024.

ICDE 2024          



Personalized PageRanks over Dynamic Graphs -- The Case for Optimizing Quality of Service.
Zulun Zhu, Siqiang Luo, Wenqing Lin°, Sibo Wang, Dingheng Mo, Chunbo Li.
Proceedings of IEEE International Conference on Data Engineering (ICDE), to appear, 2024.

TKDE 2024          



Efficient Algorithms for Group Hitting Probability Queries on Large Graphs.
Qintian Guo, Dandan Lin, Sibo Wang, Raymond Chi-Wing Wong, Wenqing Lin°.
IEEE Transactions on Knowledge and Data Engineering (TKDE), to appear, 2024.

SIGKDD 2023          



Constrained Social Community Recommendation. [video]
Xingyi Zhang˚, Shuliang Xu°, Wenqing Lin°, Sibo Wang.
Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 5586-5596, 2023.

SIGKDD 2023          



Capacity Constrained Influence Maximization in Social Networks. [code, video]
Shiqi Zhang˚, Yiqian Huang, Jiachen Sun°, Wenqing Lin°, Xiaokui Xiao, Bo Tang.
Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 3376-3385, 2023.

SIGMOD 2023          



Managing Conflicting Interests of Stakeholders in Influencer Marketing.
Shixun Huang˚, Junhao Gan, Zhifeng Bao, Wenqing Lin°.
Proceedings of the ACM on Management of Data (PACMMOD), 1(1): 80:1-80:27, 2023.

PVLDB 2022          



Influence Maximization in Real-World Closed Social Networks. [code]
Shixun Huang˚, Wenqing Lin°, Zhifeng Bao, Jiachen Sun°.
Proceedings of the VLDB Endowment (PVLDB), 16(2): 180-192, 2022.

CIKM 2022          



Measuring Friendship Closeness: A Perspective of Social Identity Theory.
Shiqi Zhang˚, Jiachen Sun°, Wenqing Lin°, Xiaokui Xiao, Bo Tang.
Proceedings of ACM International Conference on Information and Knowledge Management (CIKM), pages 3664-3673, 2022.

TODS 2022          



Influence Maximization Revisited: Efficient Sampling with Bound Tightened.
Qintian Guo, Sibo Wang, Zhewei Wei, Wenqing Lin°, Jing Tang.
ACM Transactions on Database Systems (TODS), 47(3): 12:1-12:45, 2022.

SIGKDD 2021          



Large-Scale Network Embedding in Apache Spark.
Wenqing Lin°.
Proceedings of ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 3271-3279, 2021.

WSDM 2020          



Initialization for Network Embedding: A Graph Partition Approach.
Wenqing Lin°, Feng He, Faqiang Zhang, Xu Cheng, Hongyun Cai.
Proceedings of ACM International Conference on Web Search and Data Mining (WSDM), pages 367-374, 2020.

TKDE 2020          



BATON: Batch One-Hop Personalized PageRanks with Efficiency and Accuracy.
Siqiang Luo, Xiaokui Xiao, Wenqing Lin°, Ben Kao.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 32(10): 1897-1908, 2020.

WWW 2019          



Distributed Algorithms for Fully Personalized PageRank on Large Graphs.
Wenqing Lin°.
Proceedings of the World Wide Web Conference (WWW), pages 1084-1094, 2019.

ICDE 2019          



Efficient Batch One-Hop Personalized PageRanks.
Siqiang Luo, Xiaokui Xiao, Wenqing Lin°, Ben Kao.
Proceedings of the 35th IEEE International Conference on Data Engineering (ICDE), pages 1562-1565, 2019.

TODS 2019          



Efficient Algorithms for Approximate Single-Source Personalized PageRank Queries.
Sibo Wang, Renchi Yang, Runhui Wang, Xiaokui Xiao, Zhewei Wei, Wenqing Lin°, Yin Yang, Nan Tang.
ACM Transactions on Database Systems (TODS), 44(4): 18:1-18:37, 2019.

News/Social Media Posts

2024-06-28: 腾讯云开发者 | 社交活动的“超级传播者”:揭秘网络影响力最大化算法在推荐中的应用
2024-06-17: 腾讯游戏学堂 | 如何在人群中找到相似的灵魂?详解入选国际顶会的游戏社群检测方案
2024-05-29: 腾讯高校合作 | 犀牛鸟硬核|上海交大-腾讯互娱社交算法团队两项联合研究成果入选数据挖掘顶会 SIGKDD 2024
2024-05-29: 腾讯游戏学堂 | 国际数据挖掘顶会收录,超越二元偏好的点击率预测模型
2024-05-29: 腾讯云开发者 | 基于SPARK的大规模网络表征算法及其在腾讯游戏中的应用
2024-05-23: 腾讯高校合作 | 犀牛鸟精英人才刘畅|带着游戏社交网络创新研究成果首获两篇 KDD
2024-05-13: 腾讯游戏学堂 | 找到组织了!详解游戏社群推荐算法如何帮你发现同好
2024-04-12: 腾讯云开发者 | 腾讯联合新加坡国立大学研发的这个传播模型,已入选WWW 2024
2022-09-22: 腾讯游戏学堂 | 从网络科学视角出发,拆解游戏世界中的玩家网络
2022-08-22: 游戏葡萄 | 腾讯分享的这套用户网络模型,可能会颠覆行业的运营思路
2022-08-19: 游戏陀螺 | 真没想到,光子对“玩家社交网络”的理解,已经这么学术了
2019-10-17: 腾讯技术工程 | 腾讯游戏自研学术成果:基于图分割的网络表征学习初始化技术
2019-01-23: 腾讯游戏学堂 | 计算机顶会WWW2019录用腾讯游戏增值服务部论文2篇

Selected Public Talks/Lectures

2024-06-22: DataFunSummit2024 | 图与推荐论坛
2022-05-16: DataFunSummit2022 | 机器学习和数据挖掘的原理与展望

Selected Awards/Honors

腾讯业务突破奖: 2019, 2021, 2022, 2023
腾讯卓越运营奖: 2021, 2022
腾讯专利奖: 2020, 2023
腾讯犀牛鸟精英人才计划-优秀学生/导师: 2022
Best Reviewers of CIKM 2021