Exploring How Personality Models Information Visualization Preferences

被引:6
作者
Alves, Tomas [1 ,2 ]
Ramalho, Barbara [1 ,2 ]
Goncalves, Daniel [1 ,2 ]
Gama, Sandra [1 ,2 ]
Henriques-Calado, Joana [3 ]
机构
[1] Univ Lisbon, INESC ID, Lisbon, Portugal
[2] Univ Lisbon, Inst Super Tecn, Lisbon, Portugal
[3] Univ Lisbon, Fac Psicol, CICPSI, Lisbon, Portugal
来源
2020 IEEE VISUALIZATION CONFERENCE - SHORT PAPERS (VIS 2020) | 2020年
关键词
Human-centered computing; Human computer interaction (HCI); HCI design and evaluation methods; User studies; Visualization; Visualization design and evaluation methods; LOCUS;
D O I
10.1109/VIS47514.2020.00047
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Recent research on information visualization has shown how individual differences act as a mediator on how users interact with visualization systems. We focus our exploratory study on whether personality has an effect on user preferences regarding idioms used for hierarchy, evolution over time, and comparison contexts. Specifically, we leverage all personality variables from the Five-Factor Model and the three dimensions from Locus of Control (LoC) with correlation and clustering approaches. The correlation-based method suggested that Neuroticism, Openness to Experience, Agreeableness, several facets from each trait, and the External dimensions from LoC mediate how much individuals prefer certain idioms. In addition, our results from the cluster-based analysis showed that Neuroticism, Extraversion, Conscientiousness, and all dimensions from LoC have an effect on preferences for idioms in hierarchy and evolution contexts. Our results support the incorporation of in-depth personality synergies with InfoVis into the design pipeline of visualization systems.
引用
收藏
页码:201 / 205
页数:5
相关论文
共 36 条
[1]   Cultural evolution and individual development of openness and conservatism [J].
Acerbi, Alberto ;
Enquist, Magnus ;
Ghirlanda, Stefano .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2009, 106 (45) :18931-18935
[2]   User Experience of Driver State Visualizations: A Look at Demographics and Personalities [J].
Braun, Michael ;
Chadowitz, Ronee ;
Alt, Florian .
HUMAN-COMPUTER INTERACTION - INTERACT 2019, PT IV, 2019, 11749 :158-176
[3]   Finding Waldo: Learning about Users from their Interactions [J].
Brown, Eli T. ;
Ottley, Alvitta ;
Zhao, Helen ;
Lin, Quan ;
Souvenir, Richard ;
Endert, Alex ;
Chang, Remco .
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2014, 20 (12) :1663-1672
[4]  
Cashman D, 2019, EVIVA ML IEEE VIS WO, V7
[5]  
Conati C, 2015, AAAI CONF ARTIF INTE, P4100
[6]  
Costa Jr P. T., 2008, REVISED NEO PERSONAL
[7]  
Costa P.T., 2008, The SAGE handbook of personality theory and assessment, V2, P179, DOI [DOI 10.4135/9781849200479.N9, 10.4135/9781849200479.n9]
[8]   Comparing the Pearson and Spearman Correlation Coefficients Across Distributions and Sample Sizes: A Tutorial Using Simulations and Empirical Data [J].
de Winter, Joost C. F. ;
Gosling, Samuel D. ;
Potter, Jeff .
PSYCHOLOGICAL METHODS, 2016, 21 (03) :273-290
[9]  
Feist G.J., 2004, EMPIR STUD ARTS, V22, P77, DOI DOI 10.2190/Y7CA-TBY6-V7LR-76GK
[10]  
Green T. M., 2010, 2010 Proceedings of IEEE Symposium on Visual Analytics Science and Technology (VAST 2010), P203, DOI 10.1109/VAST.2010.5653587