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How does the implementation of recommendation strategies impact user creation on digital content platforms?

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The implementation of recommendation strategies significantly influences user behavior on digital content platforms. Users strategically consume content to shape future recommendations, engaging in behaviors that accentuate their differences from others and potentially avoiding mainstream content. Content creators compete for exposure, impacting user welfare, but a relevance-driven approach can perform well in the long run, especially when users' decisions involve randomness and the platform offers diverse alternatives. Machine learning applications, like recommendation systems, play a crucial role in retaining customers by suggesting personalized content. To enhance recommendation quality, strategies such as using prior preferences, avoiding universally liked content, and providing personalized yet appealing recommendations can be effective. Overall, strategic user behavior and competition among content creators shape the effectiveness and impact of recommendation strategies on digital content platforms.

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Open access•Posted Content•DOI How Bad is Top-$K$ Recommendation under Competing Content Creators? 03 Feb 2023	The implementation of top-$K$ recommendation strategies influences user welfare by bounding user welfare loss due to creator competition, favoring relevance-driven matching in the long run.
Open access•Posted Content•DOI Recommending to Strategic Users 13 Feb 2023	Implementation of recommendation strategies influences user behavior on digital platforms by revealing that users strategically consume content to shape future recommendations, leading to accentuated differences and potential minority content neglect.
Journal Article•DOI Recommending to Strategic Users Andrea B. Haupt, Dylan Hadfield-Menell, Chara Podimata - Show less +2 more 13 Feb 2023-arXiv.org	Strategic user behavior influences content consumption to shape future recommendations. Implementing prior preferences, avoiding mainstream content, and providing personalized yet appealing content can enhance recommendation quality.
Journal Article•DOI How Bad is Top-K Recommendation under Competing Content Creators? Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu - Show less +4 more 03 Feb 2023-arXiv.org 4 Citations	The implementation of top-K recommendation strategies influences user welfare on digital content platforms, with relevance-driven matching showing promise in maintaining user satisfaction in the long run.

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