Towards a systematic understanding of graphical cues in communication through statistical graphs

Date

2014-04-01

Author

Acartürk, Cengiz

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Statistical graphs in particular, line graphs and bar graphs are efficient means of communication in a wide range of non-expert settings. In communication settings, statistical graphs do not only serve as visualizations of individual data points but also provide visual access to various aspects of the information contained in data. Moreover, specific types of graphs are better means for providing visual access to certain aspects of data. For instance, trend information is visually conveyed through line graphs and bar graphs in the time domain. The interpretation of the information content in a graph is influenced by several factors, such as perceptual salience of line segments in a line graph. In addition, the presence of graphical cues substantially influences the interpretation of graph readers. Graphical cues are visual elements, usually in the form of point markers, non-directional lines, curves and arrows. They play a communicative role in communication through graphs. The present study reports an experimental investigation, in which the participants provided verbal descriptions of a set of graphs with/without graphical cues. The stimuli involved line graphs and bar graphs that represented the same data. The analyses of eye movements and verbal protocols reveal that the interpretations of the participants are systematically influenced by the presence or absence of a graphical cue, the type of the graphical cue (i.e., a point marker vs. an arrow), as well as the type of the graph (i.e., a line graph vs. a bar graph).

Subject Keywords

Statistical graphs, Line graphs, Bar graphs, Graphical cues, Verbal protocols, Eye movements

URI

https://hdl.handle.net/11511/35151

Journal

JOURNAL OF VISUAL LANGUAGES AND COMPUTING

DOI

https://doi.org/10.1016/j.jvlc.2013.11.006

Collections

Graduate School of Informatics, Article

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Citation Formats

C. Acartürk, “Towards a systematic understanding of graphical cues in communication through statistical graphs,” JOURNAL OF VISUAL LANGUAGES AND COMPUTING, pp. 76–88, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/35151.