Überwindung Selektiver Exposition bei der Websuche durch Berücksichtigung von Augenbewegungen und physiologischen Signalen (ECHOES)
The amount of information on the web is ever-increasing, so people
develop strategies to select important news and information and avoid cognitive
load. Thereby, people prefer selecting and reading information that is
consistent with their own. This phenomenon is explained by the psychological
concepts of “selective exposure” and “confirmation bias” which can negatively
affect personal decision-making and might lead to misjudgments.
In this project, we will combine knowledge from the research areas of
interactive information retrieval, knowledge discovery, and human-computer
interaction to investigate options for counteracting selective exposure on the
web. The overall goal is to support users in overcoming selective exposure
behavior and make suggestions to inform themselves holistically about a topic.
Our goals are the following: (1) Investigating how selective exposure manifests
itself in interaction, behavioral, eye-tracking, and physiological data. (2)
Based on this data, examining machine learning models for real-time detection
of selective exposure. (3) Exploring how user interface components should be
designed to make the users aware of selective exposure and motivate them to
consume news with different thematic aspects of the overall topic.
To this end, we first collect interaction, behavioral, eye-tracking, and
physiological data in two lab studies. In the first study, we look at
selective exposure during exploratory web search in a real-world setting. In
the second study, we focus primarily on the aspect of reading news in a
controlled environment to collect further physiological data accompanying the
reading of articles that either confirm or contradict one's opinion. Second, we
build a software pipeline to detect selective exposure based on behavioral data
automatically. This includes a component that automatically identifies which
aspects of an overall topic have been consumed by participants and which have
not. Third, we want to provide meaningful awareness components that make
selective exposure perceptible and point users to supplemental aspects.
Therefore, we will evaluate different interaction designs with users. In the
final step, we will combine all insights and developed components and conduct a
user study in which selective exposure behavior in real-world web sessions is
automatically detected and the participant is made aware of it.