Networks for AB Testing
Data Skeptic25 Nov 2024

Networks for AB Testing

In this episode, the data scientist Wentao Su shares his experience in AB testing on social media platforms like LinkedIn and TikTok.

We talk about how network science can enhance AB testing by accounting for complex social interactions, especially in environments where users are both viewers and content creators. These interactions might cause a "spillover effect" meaning a possible influence across experimental groups, which can distort results.

To mitigate this effect, our guest presents heuristics and algorithms they developed ("one-degree label propagation") to allow for good results on big data with minimal running time and so optimize user experience and advertiser performance in social media platforms.

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The Data Skeptic Podcast features conversations with topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches. This first episode is a short discussion about what this podcast is all about.

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