8 citations · 10 across the 5 of their papers we have counts for
5 papers
Ideological Isolation in Online Social Networks: A Survey of Computational Definitions, Metrics, and Mitigation Strategies
Xiaodan Wang, Yanbin Liu, Shiqing Wu +4
The proliferation of online social networks has significantly reshaped the way individuals access and engage with information. While these platforms offer unprecedented connectivit…
Multi-Cause Deconfounding for Recommender Systems with Latent Confounders
Zhirong Huang, Shichao Zhang, Debo Cheng +3
In recommender systems, various latent confounding factors (e.g., user social environment and item public attractiveness) can affect user behavior, item exposure, and feedback in d…
Balancing Information Perception with Yin-Yang: Agent-Based Information Neutrality Model for Recommendation Systems
Mengyan Wang, Yuxuan Hu, Shiqing Wu +3
While preference-based recommendation algorithms effectively enhance user engagement by recommending personalized content, they often result in the creation of ``filter bubbles''.…
BHEISR: Nudging from Bias to Balance -- Promoting Belief Harmony by Eliminating Ideological Segregation in Knowledge-based Recommendations
Mengyan Wang, Yuxuan Hu, Zihan Yuan +4
In the realm of personalized recommendation systems, the increasing concern is the amplification of belief imbalance and user biases, a phenomenon primarily attributed to the filte…
ABEM: An Adaptive Agent-based Evolutionary Approach for Mining Influencers in Online Social Networks
Weihua Li, Yuxuan Hu, Shiqing Wu +2
A key step in influence maximization in online social networks is the identification of a small number of users, known as influencers, who are able to spread influence quickly and…