National Repository of Grey Literature 1 records found  Search took 0.00 seconds. 
Detecting Misleading Features in Data Visualization
Roubalová, Hana ; Vomlelová, Marta (advisor) ; Červíčková, Věra (referee)
This thesis explores the identification and detection of misleading elements in data visu- alizations. The theoretical portion focuses on understanding various types of misleading features commonly encountered in scientific figures and recognizing them. The imple- mentation introduces an application designed to detect colorblind-unfriendly graphs with the analysis of various algorithms. The thesis raises awareness about misleading visual- izations and demonstrates how software can simplify the detection of misleading features for the everyday user. This thesis highlights the importance of addressing misleading features in data visualizations and introduces an application to assist in their detection. The study advances our understanding of this field and offers insights into reducing the negative effects of misleading data visualizations. 1

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