The Impact of Personality and Demographic Variables in Collaborative Filtering of User Interest on Social Media

Marwa M. Alrehili, Wael M. S. Yafooz, Abdullah Alsaeedi, Abdel-hamid M. Emara, Aldosary Saad, Hussain Al Aqrabi

Research output: Contribution to journalArticlepeer-review


The advent of social networks and micro-blogging sites online has led to an abundance of user-generated content. Hence, the enormous amount of content is viewed as inappropriate and unimportant information by many users on social media. Therefore, there is a need to use personalization to select information related to users’ interests or searchers on social media platforms. Therefore, in recent years, user interest mining has been a prominent research area. However, almost all of the emerging research suffers from significant gaps and drawbacks. Firstly, it suffers from focusing on the explicit content of the users to determine the interests of the users while neglecting the multiple facts as the personality of the users; demographic data may be a valuable source of influence on the interests of the users. Secondly, existing work represents users with their interesting topics without considering the semantic similarity between the topics based on clusters to extract the users’ implicit interests. This paper is aims to propose a novel user interest mining approach and model based on demographic data, big five personality traits and similarity between the topics based on clusters. To demonstrate the leverage of combining user personality traits and demographic data into interest investigation, various experiments were conducted on the collected data. The experimental results showed that looking at personality and demographic data gives more accurate results in mining systems, increases utility, and can help address cold start problems for new users. Moreover, the results also showed that interesting topics were the dominant factor. On the other hand, the results showed that the current users’ implicit interests can be predicted through the cluster based on similar topics. Moreover, the hybrid model based on graphs facilitates the study of the patterns of interaction between users and topics. This model can be beneficial for researchers, people on social media, and for certain research in related fields.
Original languageEnglish
Article number2157
Number of pages31
JournalApplied Sciences
Issue number4
Publication statusPublished - 18 Feb 2022


Dive into the research topics of 'The Impact of Personality and Demographic Variables in Collaborative Filtering of User Interest on Social Media'. Together they form a unique fingerprint.

Cite this