Ranking social media news feeds: A comparative study of Personalized and Non-Personalized prediction models
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Date
2022-01-24
Journal Title
Journal ISSN
Volume Title
Publisher
University of Eloued جامعة الوادي
Abstract
Ranking news feed updates by relevance has been proposed
to help social media users catch up with the content they may nd inter-
esting. For this matter, a single non-personalized model has been used
to predict the relevance for all users. However, as user interests and pref-
erences are di erent, we believe that using a personalized model for each
user is crucial to re ne the ranking. In this work, to predict the relevance
of news feed updates and improve user experience, we use the random
forest algorithm to train and introduce a personalized prediction model
for each user. Then, we compare personalized and non-personalized mod-
els according to six criteria: (1) the overall prediction performance; (2)
the amount of data in the training set; (3) the cold-start problem; (4)
the incorporation of user preferences over time; (5) the model ne-tuning;
and (6) the personalization of feature importance for users. Experimen-
tal results on Twitter show that a single non-personalized model for all
users is easy to manage and ne-tune, is less likely to over t, and it ad-
dresses the problem of cold-start and inactive users. On the other hand,
the personalized models we introduce allow personalized feature impor-
tance, take into consideration the preferences of each user, and allow to
track changes in user preferences over time. Furthermore, personalized
models give a higher prediction accuracy than non-personalized models.
Description
Forum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of Eloued
Keywords
Social media, News feed, Relevance, Personalization
Citation
Belkacem,Sami. Boukhalfa, Kamel. Boussaid, Omar. Penguins Search Optimization Algorithm (PeSOA) for chaotic synchronization system. Forum of Artificial Intelligence and Its Applications. 24-26 Jan 2022. Faculty of Exat science. University of Eloued. [visited in ../../….]. available from [copy the link here]