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- surveyJune 2024
A Survey of Graph Neural Networks for Social Recommender Systems
ACM Computing Surveys (CSUR), Volume 56, Issue 10Article No.: 265, Pages 1–34https://doi.org/10.1145/3661821Social recommender systems (SocialRS) simultaneously leverage the user-to-item interactions as well as the user-to-user social relations for the task of generating item recommendations to users. Additionally exploiting social relations is clearly ...
- research-articleMay 2024
Corrective or Backfire: Characterizing and Predicting User Response to Social Correction
WEBSCI '24: Proceedings of the 16th ACM Web Science ConferenceMay 2024, Pages 149–158https://doi.org/10.1145/3614419.3644004Online misinformation poses a global risk with harmful implications for society. Ordinary social media users are known to actively reply to misinformation posts with counter-misinformation messages, which is shown to be effective in containing the spread ...
Better to Ask in English: Cross-Lingual Evaluation of Large Language Models for Healthcare Queries
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 2627–2638https://doi.org/10.1145/3589334.3645643Large language models (LLMs) are transforming the ways the general public accesses and consumes information. Their influence is particularly pronounced in pivotal sectors like healthcare, where lay individuals are increasingly appropriating LLMs as ...
- research-articleOctober 2023
Representation Learning in Continuous-Time Dynamic Signed Networks
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge ManagementOctober 2023, Pages 2229–2238https://doi.org/10.1145/3583780.3615032Signed networks allow us to model conflicting relationships and interactions, such as friend/enemy and support/oppose. These signed interactions happen in real-time. Modeling such dynamics of signed networks is crucial to understanding the evolution of ...
- research-articleAugust 2023
Predicting Information Pathways Across Online Communities
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 1044–1056https://doi.org/10.1145/3580305.3599470The problem of community-level information pathway prediction (CLIPP) aims at predicting the transmission trajectory of content across online communities. A successful solution to CLIPP holds significance as it facilitates the distribution of valuable ...
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- abstractAugust 2023
3rd Workshop on Online and Adaptive Recommender Systems (OARS)
- Xiquan Cui,
- Vachik Dave,
- Yi Su,
- Khalifeh Al-Jadda,
- Srijan Kumar,
- Julian McAuley,
- Tao Ye,
- Stephen D. Guo,
- Chip Huyen
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 5855–5856https://doi.org/10.1145/3580305.3599219Recommender systems (RecSys) play important roles in helping users navigate, discover, and consume large and highly dynamic information. Today, many RecSys solutions deployed in the real world rely on categorical user-profiles and/or pre-calculated ...
- research-articleAugust 2023
Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 2023–2035https://doi.org/10.1145/3580305.3599517Real-world graphs such as social networks, communication networks, and rating networks are constantly evolving over time. Many deep learning architectures have been developed to learn effective node representations using both graph structure and ...
- research-articleJune 2023
Graph Vulnerability and Robustness: A Survey
IEEE Transactions on Knowledge and Data Engineering (IEEECS_TKDE), Volume 35, Issue 6June 2023, Pages 5915–5934https://doi.org/10.1109/TKDE.2022.3163672The study of network robustness is a critical tool in the characterization and sense making of complex interconnected systems such as infrastructure, communication and social networks. While significant research has been conducted in these areas, gaps in ...
- research-articleApril 2023
Characterizing and Predicting Social Correction on Twitter
WebSci '23: Proceedings of the 15th ACM Web Science Conference 2023April 2023, Pages 86–95https://doi.org/10.1145/3578503.3583610Online misinformation has been a serious threat to public health and society. Social media users are known to reply to misinformation posts with counter-misinformation messages, which have been shown to be effective in curbing the spread of ...
- research-articleApril 2023
Reinforcement Learning-based Counter-Misinformation Response Generation: A Case Study of COVID-19 Vaccine Misinformation
WWW '23: Proceedings of the ACM Web Conference 2023April 2023, Pages 2698–2709https://doi.org/10.1145/3543507.3583388The spread of online misinformation threatens public health, democracy, and the broader society. While professional fact-checkers form the first line of defense by fact-checking popular false claims, they do not engage directly in conversations with ...
- research-articleFebruary 2023
Advances in AI for safety, equity, and well-being on web and social media: detection, robustness, attribution, and mitigation
AAAI'23/IAAI'23/EAAI'23: Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial IntelligenceFebruary 2023, Article No.: 1742, Page 15444https://doi.org/10.1609/aaai.v37i13.26811 - research-articleJanuary 2023
M2P2: Multimodal Persuasion Prediction Using Adaptive Fusion
IEEE Transactions on Multimedia (TOM), Volume 252023, Pages 942–952https://doi.org/10.1109/TMM.2021.3134168Identifying persuasive speakers in an adversarial environment is a critical task. In a national election, politicians would like to have persuasive speakers campaign on their behalf. When a company faces adverse publicity, they would like to engage ...
- short-paperOctober 2022
Implicit Session Contexts for Next-Item Recommendations
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementOctober 2022, Pages 4364–4368https://doi.org/10.1145/3511808.3557613\noindent Session-based recommender systems capture the short-term interest of a user within a session. Session contexts (i.e., a user's high-level interests or intents within a session) are not explicitly given in most datasets, and implicitly ...
- research-articleOctober 2022
Rank List Sensitivity of Recommender Systems to Interaction Perturbations
CIKM '22: Proceedings of the 31st ACM International Conference on Information & Knowledge ManagementOctober 2022, Pages 1584–1594https://doi.org/10.1145/3511808.3557425Prediction models can exhibit sensitivity with respect to training data: small changes in the training data can produce models that assign conflicting predictions to individual data points during test time. In this work, we study this sensitivity in ...
- short-paperSeptember 2022
M2TRec: Metadata-aware Multi-task Transformer for Large-scale and Cold-start free Session-based Recommendations
RecSys '22: Proceedings of the 16th ACM Conference on Recommender SystemsSeptember 2022, Pages 573–578https://doi.org/10.1145/3523227.3551477Session-based recommender systems (SBRSs) have shown superior performance over conventional methods. However, they show limited scalability on large-scale industrial datasets since most models learn one embedding per item. This leads to a large memory ...
- abstractAugust 2022
Joint International Workshop on Misinformation and Misbehavior Mining on the Web & Making a Credible Web for Tomorrow (MIS2-TrueFact)
- Pamela Bhattacharya,
- Jing Gao,
- Meng Jiang,
- Mehran Kafai,
- Srijan Kumar,
- Qi Li,
- Neil Shah,
- Sihong Xie,
- Philip S. Yu,
- Ming Zeng
KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2022, Pages 4854–4855https://doi.org/10.1145/3534678.3542898The MIS2-TrueFact is geared towards bringing academic, industry, and government researchers and practitioners together to tackle the challenges in misinformation, misbehavior, and data quality issues on the web with heterogeneous and multi-modal sources ...
- abstractAugust 2022
2nd Workshop on Online and Adaptive Recommender Systems (OARS)
- Xiquan Cui,
- Vachik Dave,
- Yi Su,
- Khalifeh Al-Jadda,
- Srijan Kumar,
- Julian McAuley,
- Tao Ye,
- Kamelia Aryafar,
- Mohammed Korayem
KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2022, Pages 4862–4863https://doi.org/10.1145/3534678.3542893Recommender systems (RecSys) play important roles in helping users navigate, discover, and consume large and highly dynamic information. Today, many RecSys solutions deployed in the real world rely on categorical user-profiles and/or pre-calculated ...
- extended-abstractAugust 2022
- research-articleApril 2022
Characterizing, Detecting, and Predicting Online Ban Evasion
WWW '22: Proceedings of the ACM Web Conference 2022April 2022, Pages 2614–2623https://doi.org/10.1145/3485447.3512133Moderators and automated methods enforce bans on malicious users who engage in disruptive behavior. However, malicious users can easily create a new account to evade such bans. Previous research has focused on other forms of online deception, like the ...
- short-paperJanuary 2022
HawkEye: a robust reputation system for community-based counter-misinformation
ASONAM '21: Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningNovember 2021, Pages 188–192https://doi.org/10.1145/3487351.3488343Twitter's Birdwatch is a new community-driven misinformation detection platform where users provide notes to label tweet accuracy, and rate the 'helpfulness' of other users' notes. This work investigates the robustness of Birdwatch against adversaries ...