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Research and Insights

Explore our Research and Insights hub, where transformative data insights and groundbreaking research drive informed decisions and accelerate progress

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March 21, 2023 | Stanford University Graduate School of Business Research Paper, Forthcoming

Multi-Objective Personalization of the Length and Skippability of Video Advertisements

In this paper, we study two features of digital video ads on content-streaming platforms: length and skippability. Working with vdo. ai, we conduct a field experiment and randomly assign users to the Skippable/Long and Non-Skippable/Short versions of the same ad. We find that compared to the Non-Skippable/Short ad, the Skippable/Long ad version in our study increases ad consumption but decreases video consumption.

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June 01, 2022 | Stanford University Graduate School of Business Research Paper, Forthcoming

Does Emotional Matching Between Video Ads and Content Lead to Better Engagement: Evidence from a Large-Scale Field Experiment∗

Modern digital advertising platforms allow ads to be targeted in a variety of ways, and generally aim to match the ad being shown with either the user or the content being shown. In this study, we examine the effect of matching in emotional content of ads and the video on which the ad is shown on consumers’ engagement with the ad.

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January 11, 2018 | Institute of Electrical and Electronics Engineers

An approach towards identification and prevention of riots by analysis of social media posts in real-time

This paper presents an approach for monitoring Facebook posts and comments in real-time, with an aim at identifying plausible riots that could spur up as a result. In this research, we employ an NLP and sentiment analysis based algorithm to classify a discussion as likely to cause a riot or not and identify the power groups involved in it.

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