Developing an Adaptive Feed Algorithm: A Case Study
1. Lucca Ferraz Vaz, University of Sao Paulo, Student, Brazil
2. Roberto Gropelli, University of Brasília, Student, Brazil
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.
Feed Algorithm Personalization Relevance Data Collection Collaborative Filtering Dynamic Ranking User Engagement
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.
1. None
The author confirms sole responsibility for the following: study conception and design, data collection, analysis and interpretation of results, and manuscript preparation.
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.
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All authors declare that they have no conflicts of interest.
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.
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