Category: Bachelor Thesis
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Analysis of the Performance of a Conversational Recommender System in Online Fashion E-Commerce
Supervisor: Julia Neidhardt, Co-Supervisor: Gwendolyn Rippberger
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Data Transformation Tool to Explore News Recommenders
Author: Manuel Feuerstein Supervisor: Julia Neidhardt, Co-Supervisor: Thomas E. Kolb Abstract This thesis focuses on the development of a data transformation tool to analyze and leverage diverse data sources from Falter Verlagsgesellschaft m.b.H (Falter). Falter provides content-based data from platforms like falter.at and shop.falter.at, along with user-based data from Matomo Analytics and shop purchase statistics.…
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Examining Tech Bias: Analyzing Career Recommendations in LLMs through Demographic Persona-Based Prompting
Supervisor: Julia Neidhardt, Co-Supervisor: Bernhard Krüpl-Sypien
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Temporal Analysis of Session Clusters in Clickstream Data from a Price Comparison Platform
Author: Luca Turin Supervisor: Julia Neidhardt, Co-Supervisor: Ahmadou Wagne Abstract Understanding user behaviour is essential for designing digital services, improving user experience, and optimising commercial outcomes. This thesis investigates how behaviour varies over time and across contexts on a major price comparison platform. Building on prior work that offered a static segmentation of sessions, it…
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Measuring Controversy in Online Discussions
Author: Ivan Andreev Supervisor: Stefan Woltran, Co-Supervisor: Julia Neidhardt Abstract In today’s digital era, analyzing and improving online discourse is crucial. Polarisation is indeed a significant issue in contemporary society, particularly amplified within online discussions. The ability to accurately measure polarisation in these contexts is crucial for understanding societal dynamics and addressing associated challenges effectively.…
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Wie wirken sich technologische Filterblasen, als Folge der algorithmisch personalisierten Aufbereitung von Inhalten sozialer Netzwerke, auf die politische Meinungspolarisierung der Nutzer:innen aus?
Author: Nadine Chincea Supervisor: Irina Nalis-Neuner, Co-Supervisor: Julia Neidhardt Abstract Die unterschiedlichen Meinungen zu technologischen Filterblasen im Internet und deren angenommenen Auswirkungen spiegeln sich nicht nur im öffentlichen Diskurs, sondern auch in der Forschungsliteratur wider. Die wesentliche Grundlage dieser Thematik bilden allerdings Fragen um die Funktionsweisen und Effekte von Personalisierungsalgorithmen. Die an die einzelnen Nutzer:innen…