相关论文: Predicting Personality from Book Preferences with …
Recommender systems have gained increasing attention to personalise consumer preferences. While these systems have primarily focused on applications such as advertisement recommendations (e.g., Google), personalized suggestions (e.g.,…
Recent studies comparing AI-generated and human-authored literary texts have produced conflicting results: some suggest AI already surpasses human quality, while others argue it still falls short. We start from the hypothesis that such…
In recent years, with the enormous explosion of web based learning resources, personalization has become a critical factor for the success of services that wish to leverage the power of Web 2.0. However, the relevance, significance and…
Online Social Networking Sites attracted a massive number of users over the past decade but also raised privacy concerns with the amount of personal information disclosed. Studies have shown that 25% of the users are not aware of privacy…
In this paper, we introduce a psychology-inspired approach to model and predict the music genre preferences of different groups of users by utilizing human memory processes. These processes describe how humans access information units in…
Popularity of content in social media is unequally distributed, with some items receiving a disproportionate share of attention from users. Predicting which newly-submitted items will become popular is critically important for both hosts of…
Social media marketing plays a vital role in promoting brand and product values to wide audiences. In order to boost their advertising revenues, global media buying platforms such as Facebook Ads constantly reduce the reach of branded…
In folksonomies, users use to share objects (movies, books, bookmarks, etc.) by annotating them with a set of tags of their own choice. With the rise of the Web 2.0 age, users become the core of the system since they are both the…
In this assignment, we examine whether there is a correlation between the personality type of a person and the texts they wrote. In order to do this, we aggregated datasets of Reddit comments labeled with the Myers-Briggs Type Indicator…
Myers-Briggs Type Indicator (MBTI) types depict the psychological preferences by which a person perceives the world and make decisions. There are 4 principal functions through which the people see the world: sensation, intuition, feeling,…
Personalized AI systems, from recommendation systems to chatbots, are a prevalent method for distributing content to users based on their learned preferences. However, there is growing concern about the adverse effects of these systems,…
With the emergence of Web 2.0, tag recommenders have become important tools, which aim to support users in finding descriptive tags for their bookmarked resources. Although current algorithms provide good results in terms of tag prediction…
In this research, we explored the efficacy of various warning label designs for AI-generated content on social media platforms e.g., deepfakes. We devised and assessed ten distinct label design samples that varied across the dimensions of…
This study analyzes the relationship between non-verbal information (e.g., genres) and text design (e.g., font style, character color, etc.) through the classification of book genres using text design on book covers. Text images have both…
With the rise in capabilities of large language models (LLMs) and their deployment in real-world tasks, evaluating LLM alignment with human preferences has become an important challenge. Current benchmarks average preferences across all…
Music listening preferences at a given time depend on a wide range of contextual factors, such as user emotional state, location and activity at listening time, the day of the week, the time of the day, etc. It is therefore of great…
Scholars, awards committees, and laypeople frequently discuss the merit of written works. Literary professionals and journalists differ in how much perspectivism they concede in their book reviews. Here, we quantify how strongly book…
This is a preprint version of the first book from the series: "Stories told by data". In this book a story is told about the psychological traits associated with drug consumption. The book includes: - A review of published works on the…
Collaborative filtering algorithms find useful patterns in rating and consumption data and exploit these patterns to guide users to good items. Many of the patterns in rating datasets reflect important real-world differences between the…
Recent studies have shown that recommendation systems commonly suffer from popularity bias. Popularity bias refers to the problem that popular items (i.e., frequently rated items) are recommended frequently while less popular items are…