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arXiv:1902.03098cs.SI

Measuring Long-term Impact of Ads on LinkedIn Feed

Jinyun Yan, Birjodh Tiwana, Souvik Ghosh, Haishan Liu, Shaunak Chatterjee

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

Organic updates (from a member's network) and sponsored updates (or ads, from advertisers) together form the newsfeed on LinkedIn. The newsfeed, the default homepage for members, attracts them to engage, brings them value and helps LinkedIn grow. Engagement and Revenue on feed are two critical, yet often conflicting objectives. Hence, it is important to design a good Revenue-Engagement Tradeoff (RENT) mechanism to blend ads in the feed. In this paper, we design experiments to understand how members' behavior evolve over time given different ads experiences. These experiences vary on ads density, while the quality of ads (ensured by relevance models) is held constant. Our experiments have been conducted on randomized member buckets and we use two experimental designs to measure the short term and long term effects of the various treatments. Based on the first three months' data, we observe that the long term impact is at a much smaller scale than the short term impact in our application. Furthermore, we observe different member cohorts (based on user activity level) adapt and react differently over time.

arXiv comments
Needs more polish
Journal reference
2018 Conference on Digital Experimentation (CODE)
DOI
Subjects
cs.SISocial and Information Networks cs.LGMachine Learning stat.MLMachine Learning (Statistics)

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Jul 2019 to Jul 2019. Found in 2 HN submissions from Feb 2019 to Jul 2019. Open submission discussions.

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Discussed in comments1 thread

    • v2 is zero bytes, but v1 works: https://arxiv.org/abs/1902.03098v1 This preprint paper contains no indication of participation by an Ethical Review Board and lists 5 @linked.com email addresses as the sole authors. How is this study ethically responsible?

      floatingatollView on HNParent context

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