05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6

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Publication Type: search.filters.UBSTyp.ZeitschriftenartikelInstitute: search.filters.UBSInstitut.Institut für Visualisierung und Interaktive SystemeAuthor: search.filters.author.Koch, Steffen

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    Case study on privacy-aware social media data processing in disaster management
    (2020) Löchner, Marc; Fathi, Ramian; Schmid, David ‘-1’; Dunkel, Alexander; Burghardt, Dirk; Fiedrich, Frank; Koch, Steffen
    Social media data is heavily used to analyze and evaluate situations in times of disasters, and derive decisions for action from it. In these critical situations, it is not surprising that privacy is often considered a secondary problem. In order to prevent subsequent abuse, theft or public exposure of collected datasets, however, protecting the privacy of social media users is crucial. Avoiding unnecessary data retention is an important question that is currently largely unsolved. There are a number of technical approaches available, but their deployment in disaster management is either impractical or requires special adaption, limiting its utility. In this case study, we explore the deployment of a cardinality estimation algorithm called HyperLogLog into disaster management processes. It is particularly suited for this field, because it allows to stream data in a format that cannot be used for purposes other than the originally intended. We develop and conduct a focus group discussion with teams of social media analysts. We identify challenges and opportunities of working with such a privacy-enhanced social media data format and compare the process with conventional techniques. Our findings show that, with the exception of training scenarios, deploying HyperLogLog in the data acquisition process will not distract the data analysis process. Instead, several benefits, such as improved working with huge datasets, may contribute to a more widespread use and adoption of the presented technique, which provides a basis for a better integration of privacy considerations in disaster management.
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    Studies and design considerations for animated transitions between small-scale visualizations
    (2023) Huth, Franziska; Blascheck, Tanja; Koch, Steffen; Ertl, Thomas
    Small-scale visualizations can augment text, show information on mobile devices, or geographical information on a map. In such situations, there is often not enough space to show complex data with approaches like juxtaposed visualizations. To alleviate this issue, we propose the use of animated transitions between several small-scale visualizations. We discuss design considerations for animated transitions between small-scale visualizations and differences to normal-sized visualizations. Further, we present the results of two online studies on the effectiveness of those animated transitions to convey information and attribute relations, as well as the mental load of following the animated transitions. As a result, we found that animated transitions between visualizations are understandable in small scale, but performance depends on the specific task and the type of operation carried out with the animated transition.