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stat.AP2024
Causal Inference in Social Platforms Under Approximate Interference Networks
Yiming Jiang, Lu Deng, Yong Wang +1
Estimating the total treatment effect (TTE) of a new feature in social platforms is crucial for understanding its impact on user behavior. However, the presence of network interfer…
cs.SI2024
Ego Group Partition: A Novel Framework for Improving Ego Experiments in Social Networks
Lu Deng, JingJing Zhang, Yong Wang +1
Estimating the average treatment effect in social networks is challenging due to individuals influencing each other. One approach to address interference is ego cluster experiments…
cs.SI2024
Unbiased Estimation for Total Treatment Effect Under Interference Using Aggregated Dyadic Data
Lu Deng, Yilin Li, JingJing Zhang +2
In social media platforms, user behavior is often influenced by interactions with other users, complicating the accurate estimation of causal effects in traditional A/B experiments…