AI recommendation vs. user subscription: Analyzing in-feed digital advertising performance on social media platforms

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AI recommendation vs. user subscription: Analyzing in-feed digital advertising performance on social media platforms
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Researchers from Lehigh University, University of Hong Kong, and Wuhan University published a new Journal of Marketing article that examines in-feed advertising's performance across subscription versus AI recommended news feeds.

Journal of Marketing

If, for example, you log into Twitter and open the"Following" tab, you will encounter posts from the sources you have subscribed to. Or if you open the"For You" tab, you will see content recommended by AI algorithms based on what AI predicts you are interested in viewing. The authors explain that"in-feed ads ideally fit seamlessly into the organic content stream and their effectiveness is determined by both the ads' attributes and where they are placed. We examine how the channel affects ad effectiveness and whether the effects also depend on ad attributes.

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