@Article{M-10064,
AUTHOR = {Vaz, Lucca Ferraz and Gropelli, Roberto},
TITLE = {Developing an Adaptive Feed Algorithm: A Case Study},
JOURNAL = {Scientific Research Journal of Science, Engineering and Technology},
VOLUME = {1},
YEAR = {2023},
NUMBER = {2},
ARTICLE-NUMBER = {M-10064},
URL = {https://isrdo.org/journal/SRJSET/currentissue/developing-an-adaptive-feed-algorithm-a-case-study},
ISSN = {2584-0584},
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.},
DOI = {}
}