Tag clouds algorithm with the inclusion of personality traits

Tag clouds have emerged as the latest technique in information visualization using text analysis methods in a variety of situations to interpret unstructured data types. Literature review emphasizes that information visualization development techniques should include the personality traits of humans...

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Main Author:	Ahmad Affandi, Supli
Format:	Thesis
Language:	eng eng
Published:	2015
Subjects:	QA75 Electronic computers Computer science
Online Access:	https://etd.uum.edu.my/5797/1/s812299_02.pdf https://etd.uum.edu.my/5797/7/s812299_01.pdf
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id	my-uum-etd.5797
record_format	uketd_dc
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Shiratuddin, Norshuhada Ab. Aziz, Azizi
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Ahmad Affandi, Supli Tag clouds algorithm with the inclusion of personality traits
description	Tag clouds have emerged as the latest technique in information visualization using text analysis methods in a variety of situations to interpret unstructured data types. Literature review emphasizes that information visualization development techniques should include the personality traits of humans to provide effective and meaningful information. However, in the field of tag clouds, no published studies have investigated the role of personality traits to guide the design of tag cloud visualization. Furthermore, the algorithm to generate tag cloud visualization based on personality traits has not been explored. Therefore, the main objective of this study is to develop an algorithm that can adapt visual features of tag cloud layout styles based on personality traits of the user. This study focuses on two visual features associated with personality traits, which are colors and shapes. To achieve the aim of this study, Design Science methodology was used through three main phases: problem identification, design of solution, and evaluation. The algorithm was developed based on three theories of personality traits, namely Myers-Briggs Type Indicator (MBTI), Shape, and Multiple Intelligence (MI). The algorithm was then tested through a black box testing. In addition, a prototype was developed to evaluate the proposed algorithm. Then, user satisfaction was conducted in order to evaluate this prototype using Q-SAFI instruments. Notable findings suggest that users are highly satisfied with colors and shapes of tag cloud as well as the overall tag cloud layout styles. The main contribution of this research is the tag cloud layout styles algorithm, which combines the concept of personality traits and characteristics of colors and shapes. This algorithm is beneficial for decision making using information visualization in which personality traits of the user are heavily inclined. Moreover, the tag cloud user’s satisfaction instrument, Q-SAFI, provides measurements for evaluating tag cloud visualization.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Ahmad Affandi, Supli
author_facet	Ahmad Affandi, Supli
author_sort	Ahmad Affandi, Supli
title	Tag clouds algorithm with the inclusion of personality traits
title_short	Tag clouds algorithm with the inclusion of personality traits
title_full	Tag clouds algorithm with the inclusion of personality traits
title_fullStr	Tag clouds algorithm with the inclusion of personality traits
title_full_unstemmed	Tag clouds algorithm with the inclusion of personality traits
title_sort	tag clouds algorithm with the inclusion of personality traits
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2015
url	https://etd.uum.edu.my/5797/1/s812299_02.pdf https://etd.uum.edu.my/5797/7/s812299_01.pdf
_version_	1747827983947661312
spelling	my-uum-etd.57972021-03-18T03:04:20Z Tag clouds algorithm with the inclusion of personality traits 2015 Ahmad Affandi, Supli Shiratuddin, Norshuhada Ab. Aziz, Azizi Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts and Sciences QA75 Electronic computers. Computer science Tag clouds have emerged as the latest technique in information visualization using text analysis methods in a variety of situations to interpret unstructured data types. Literature review emphasizes that information visualization development techniques should include the personality traits of humans to provide effective and meaningful information. However, in the field of tag clouds, no published studies have investigated the role of personality traits to guide the design of tag cloud visualization. Furthermore, the algorithm to generate tag cloud visualization based on personality traits has not been explored. Therefore, the main objective of this study is to develop an algorithm that can adapt visual features of tag cloud layout styles based on personality traits of the user. This study focuses on two visual features associated with personality traits, which are colors and shapes. To achieve the aim of this study, Design Science methodology was used through three main phases: problem identification, design of solution, and evaluation. The algorithm was developed based on three theories of personality traits, namely Myers-Briggs Type Indicator (MBTI), Shape, and Multiple Intelligence (MI). The algorithm was then tested through a black box testing. In addition, a prototype was developed to evaluate the proposed algorithm. Then, user satisfaction was conducted in order to evaluate this prototype using Q-SAFI instruments. Notable findings suggest that users are highly satisfied with colors and shapes of tag cloud as well as the overall tag cloud layout styles. The main contribution of this research is the tag cloud layout styles algorithm, which combines the concept of personality traits and characteristics of colors and shapes. This algorithm is beneficial for decision making using information visualization in which personality traits of the user are heavily inclined. Moreover, the tag cloud user’s satisfaction instrument, Q-SAFI, provides measurements for evaluating tag cloud visualization. 2015 Thesis https://etd.uum.edu.my/5797/ https://etd.uum.edu.my/5797/1/s812299_02.pdf text eng public https://etd.uum.edu.my/5797/7/s812299_01.pdf text eng public masters masters Universiti Utara Malaysia Aamodt, Agnar, & Plaza, Enric. (1994). Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI communications, 7(1), 39-59. Abbas, Ali, Hoffmann, Nathan, Howard, Ronald, & Spetzler, Chris. (2007). Teaching decision skills to troubled teens. OR MS TODAY, 34(4), 48. Abraham, Ajith. (2005). 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Tag clouds algorithm with the inclusion of personality traits

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