# Applying Recommender Systems to Predict Personalized Film Age Ratings for Parents
## 1 Introduction  
Extensive research has explored how media consumption and audiovisual content affect children. The literature indicates that a child's psychological development is likely influenced by emotional stages and social factors [1; 2; 3; 4]. Media influences children and adolescents according to the amount and type of content consumed, as well as factors such as age, genetics, interpersonal relationships, context, and societal influences [5; 6; 7].  
Given that media content--such as sex, violence, or substance abuse--is generally considered inappropriate for children and adolescents, it is essential to classify films based on their suitability for different audiences. This classification is provided by age rating systems for films that are designed to inform viewers, particularly parents, about the suitability of the content of a movie for different age groups. These systems, used by organizations such as the Motion Picture Association (MPA) [8] and Common Sense Media (CSM) [9], evaluate elements such as violence, language, sexual content, and thematic material. By assigning films to categories like \"PG\" (Parental Guidance) or \"R\" (Restricted), age ratings help audiences make informed decisions about what is appropriate for children, teens, and adults to watch. Although these systems aim for consistency, cultural differences often lead to variations in ratings between countries. Parents often rely on media content classification systems, such as those provided by Common Sense Media [9], to help decide which films are appropriate for their children.  
In countries like Australia, Canada, and Singapore, official government bodies determine the ratings, while in other countries such as Denmark, Japan, and the United States, industry committees handle the process with little to no official government involvement. However, there are differences between these media content classification systems as well as between countries that have applied them in films. However, since parents are responsible for preventing or not allowing films to be seen by their children, it makes sense to create a recommender system that can provide personalized age ratings based on the parents' beliefs about the content of media for unseen films.  
In this work, we apply recommender systems to predict personalized film age ratings for parents. This approach frames the problem as a'multiple recommendation task' by using a recommender system that categorizes by age. In this work, we use the Common Sense Media dataset, where the age categories are \(AC=\{2,3,\ldots,18\}\). Multiple recommender systems provide recommendations for each age category (\(\{2,3,\ldots,18\}\)) of a film. The system then predicts age recommendations for each category, which are combined to generate the final personalized recommendation for the parent. To our knowledge, this is the first work that solves the prediction problem of personalized film age ratings. Figure 1 shows the graphical abstract of the proposed system (multiple recommender systems--MRSs) with training and testing phases. Figure 2 illustrates the schematic representation of the proposed system architecture.  
This paper is structured as follows: Section 2 reviews the related work for age rating systems and recommender systems. Section 3 introduces the main problem formulation surrounding a personalized film age rating (PFAR) that we study in this paper. Section 4 presents the proposed framework for the PFAR problem based on parental age ratings. Section 5 describes the experimental setup along with the results obtained. Finally, our conclusions are presented in Section 6.  
Figure 1: The graphical abstract of the proposed system (multiple recommender systems—MRSs) with training and testing phases.