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20212026
most citedDark Patterns in Online Shopping: Of Sneaky Tricks, Perceived Annoyance and Respective Brand Trust

29 citations · 64 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2026★ 1 cited

Splitting User Stories Into Tasks with AI -- A Foe or an Ally?

Luka Pavlič, Reinhard Bernsteiner, Stephan Schlögl +1

In agile software development, breaking down user stories into actionable tasks is a critical yet time-consuming process. This paper investigates the potential of Generative AI too…

cs.HC2023★ 16 cited

Tell me, what are you most afraid of? Exploring the Effects of Agent Representation on Information Disclosure in Human-Chatbot Interaction

Anna Stock, Stephan Schlögl, Aleksander Groth

Self-disclosure counts as a key factor influencing successful health treatment, particularly when it comes to building a functioning patient-therapist-connection. To this end, the…

cs.HC2023★ 12 cited

Chatbots for Robotic Process Automation: Investigating Perceived Trust and User Satisfaction

Alessandro Casadei, Stephan Schlögl, Markus Bergmann

Driven by ongoing improvements in machine learning, chatbots have increasingly grown from experimental interface prototypes to reliable and robust tools for process automation. Bui…

cs.HC2022★ 6 cited

Keep on Running! An Analysis of Running Tracking Application Features and their Potential Impact on Recreational Runner's Intrinsic Motivation

Dorothea Gute, Stephan Schlögl, Aleksander Groth

Physical activity is known to help improve and maintain one's health. In particular, recreational running has become increasingly popular in recent years. Yet, lack of motivation o…

cs.HC2021★ 29 cited

Dark Patterns in Online Shopping: Of Sneaky Tricks, Perceived Annoyance and Respective Brand Trust

Christian Voigt, Stephan Schlögl, Aleksander Groth

Dark patterns utilize interface elements to trick users into performing unwanted actions. Online shopping websites often employ these manipulative mechanisms so as to increase thei…