Category: Bachelor Thesis

  • How Can Digital Nudges Guide Users Towards More Diverse News Consumption?

    Author: Laura Valentina Modre Supervisor: Irina Nalis-Neuner, Co-Supervisor: Julia Neidhardt Abstract Most web-based news outlets employ recommendation algorithms which collect and process data on users’ previous behaviors and preferences to curate highly personalized news environments. Increasingly, there is a call for these systems to also incorporate insights from behavioral science to construct recommender systems that…

  • Diversity in News Recommendations- Towards a Broader Perspective on Diversity-Aware-Recommender-Systems and Their Influence on Users

    Author: Linda Basso Supervisor: Irina Nalis-Neuner, Co-Supervisor: Julia Neidhardt Abstract All of us encounter recommender systems (RS) regularly by using social media, google, online-shopping, streaming music, reading the news online, etc. The interaction with these information filtering systems is part of our everyday lives. Thus, they have an influence on their users’ behavior, their decision…

  • Improving Trust in Recommender Systems through Context Clues

    Author: Tobias Sippl Supervisor: Irina Nalis-Neuner, Co-Supervisor: Julia Neidhardt 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 confined…

  • Exploring the Sentiment Patterns of Clustered COVID-19 News Articles on Mask Requirements: A Comparison with User Comments

    Author: Lukas Burtscher Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Während die COVID-19-Pandemie weiterhin die Welt heimsucht, ist es für EntscheidungsträgerInnen und öffentliche GesundheitsbeamtInnen entscheidend, die öffentliche Stimmung und Einstellung gegenüber den Maßnahmen zur Kontrolle ihrer Ausbreitung zu verstehen. Diese Arbeit untersucht die Entwicklung der Stimmung bezüglich COVID-19-Maskenanforderungen von Januar 2020 bis Dezember 2021…

  • Content-Based Restaurant Recommendation Systems Using Textual and Visual Data

    Author: Dante Godolja Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract Content-based restaurant recommender systems use features such as cuisine type, price range, and location to suggest dining options to users. By analyzing the content of restaurants, these systems can generate recommendations. Current research explores ways to improve their effectiveness. In this thesis we explore…

  • 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…