Category: Research

  • Exploring Group Fairness in News Media Recommendations: Algorithms, Metrics, and Grouping

    Author: Blake Huebner Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Beyond accuracy metrics, such as fairness and diversity, have become widely studied topics in recommender systems. Improving these metrics is important not only from an ethical and legal perspective, but can also improve overall user satisfaction. Although fairness and diversity metrics are widely discussed,…

  • COVID-19 and Populism in Austrian News User Comments – A Machine Learning Approach

    Author: Ahmadou Wagne Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract The COVID-19 pandemic and the resulting government measures have triggered a wave of protests and demonstrations in Austria. We saw some protestors resorting to populist rhetoric to express their dissatisfaction, which in some cases, led to anti-democratic tendencies. Populist talking points have not been…

  • K-Means Clustering of Fashion Behavior: A Language-Focused Approach

    Author: Florian Dedov Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Die Analyse von kundenbezogenen E-Commerce-Daten wird zunehmend wichtiger. Die meisten Analysen in diesem Bereich fokussieren sich auf die Produkte, wobei die Analyse des tatsächlichen Benutzerverhaltens oftmals zu kurz kommt. Um jedoch Kundengruppen besser ansprechen und wirklich verstehen zu können, was deren Präferenzen und Beweggründe…

  • Merging the Gap Between Automated and Human Centered Usability Testing

    Author: Can Özgür Yilmaz Supervisor: Allan Hanbury, Co-Supervisor: Julia Neidhardt Abstract In today’s world, usability testing is an essential aspect of the software developmentprocess. Conventional usability testing however is very time and resource consuming,because there needs to be a real person observing the user and trying to discover usabilityproblems from their observations. As a solution…

  • Exhibit Rating Prediction and Visitor Path Prediction in a Museum Setting

    Author: Marek Furka Supervisor: Julia Neidhardt Abstract Rating prediction and path prediction tasks in a museum/exhibition setting are important problems, yet not well explored. Existing literature is limited and authors rarely compare multiple approaches, leaving an apparent research gap. In this study, we aim to close this research gap by giving a comprehensive comparison of…

  • Dynamic Sentiment Analysis for Measuring Media Bias

    Author: Thomas E. Kolb Supervisor: Julia Neidhardt, Co-Supervisor: Hannes Werthner Abstract Analyzing the sentiments of texts in the field of social news and news media is a big area of interest for many researchers around the world. It is a well-known problem to “teach” machines to understand the sentiments of texts e.g. news media. This…