Predicting popularity of online products via collective recommendations

Cheng-Jun Zhang, Xue-lian Zhu, Wen-bin Yu, Jin Liu, Ya-dang Chen, Yu Yao and Su-xun Wang

Physica A: Statistical Mechanics and its Applications, 2024, vol. 641, issue C

Abstract: Predicting the future popularity of commodities has always been a significant issue in information filtering research. Existing methods predominantly rely on the historical popularity of products, assuming that historically popular items will continue to be popular in the future due to preferential attachment. However, this method has limitations as it neglects the intricate structural information within the bipartite networks connecting users and items. The prediction method based on preferential attachment fails for commodities with the same degree of popularity. In this paper, we propose a popularity prediction method that aggregates user recommendation results to forecast item popularity. The method is general and applicable to any recommendation algorithm. For simplicity, we validate the method using the classic collaborative filtering algorithm. Experiments demonstrate that this method significantly outperforms the preferential attachment predictor in accurately predicting the future popularity of niche commodities.

Keywords: Bipartite network; Preferential attachment; Collaborative filtering; Recommendation-based predictor (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437124002401
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:641:y:2024:i:c:s0378437124002401

DOI: 10.1016/j.physa.2024.129731

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().