Personalised video recommendation system and its potential role as a trigger of addiction

Abstract

The influence of search engine algorithms on society’s collective thinking is significant. Initially, engineers aimed to develop algorithms that would provide optimal results for relevant keywords. However, the focus later shifted towards implementing personalised search methods that could deliver the best results tailored to individual users. Personalised search is a feature designed to enhance user engagement by analyzing and profiling their previous search interests, with or without explicit user consent. Through advanced technology and refined machine learning techniques, popular websites and applications store and analyse user preferences. For content developers, particularly those offering video content, the primary goal of personalised search algorithms is to increase users’ time spent on pages. However, the psychological consequences of this approach remain ambiguous, as it could heighten vulnerability to dependency signals and trigger a fascination with appealing behavioral patterns. This is especially problematic for individuals who are already dependent on specific habits, such as internet addiction, gaming, pornography addiction, or obesity, and are striving to limit their susceptibility to dependency signals. For instance, if a person with obesity is advised to watch videos featuring food-related cues, it might hinder their ability to restrict food consumption. To explore the potential repercussions of personalised search recommendation systems on dependency, prior research has been analysed in this study. Taking into consideration the proposed mechanisms of dependency, addressing these aspects becomes essential to mitigate the risk of undesired influence from captivating dependency signals. Thus, this study aimed to scrutinize the relationship between personalised search and the emergence of dependency, shedding light on this crucial issue