Developing an Adaptive Feed Algorithm: A Case Study

Title

Developing an Adaptive Feed Algorithm: A Case Study

Author

1. Lucca Ferraz Vaz, Student, University of Sao Paulo, Brazil
2. Roberto Gropelli, Student, University of Brasília, Brazil

Abstract

This case study delves into the evolution of a feed algorithm for Company X, a social media platform aiming to enhance user engagement. The transition from a chronological feed to a personalized and dynamic algorithm involved a multifaceted approach. Key objectives included personalization, relevance, diversity, and real-time adaptability. The process involved data collection, content analysis, user behavior modeling, collaborative filtering, dynamic ranking, and A/B testing. Challenges, such as data privacy, algorithm bias, and scalability, were addressed through anonymization, diversity incorporation, and scalable infrastructure. The results demonstrated a substantial increase in user engagement, affirming the efficacy of the adaptive feed algorithm. This case study underscores the importance of a holistic and iterative approach to algorithm development for sustained user satisfaction in the digital content landscape.

Keywords

Conclusion

Building an effective feed algorithm requires a holistic approach that considers user data, content analysis, and real-time user interactions. Continuous testing, iteration, and a commitment to addressing challenges ensure that the algorithm evolves with user needs and platform growth. The success of Company X demonstrates the importance of investing in algorithm development to enhance user experience in the dynamic landscape of digital content consumption.

Author Contrubution

The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.

Funding

The authors did not receive any specific grants from funding agencies in the public, commercial, or non-profit sectors for the research, authorship, and/or publication of this article.

Conflict of Interest

All authors declare that they have no conflicts of interest.

Data Sharing Statement

Not applicable

Software And Tools Use

Not applicable

Acknowledgements

I thank the following individuals for their expertise and assistance in all aspects of our study and for their help in writing the manuscript. I am also grateful for the insightful comments given by anonymous peer reviewers. Everyone's generosity and expertise have improved this study in myriad ways and saved me from many errors.