Task-based Quantitative Evaluation of the Concordance Mosaic Visualization

Shane Sheehan; Masood Masoodian; Saturnino Luz

doi:10.1109/IV56949.2022.00028

Task-based Quantitative Evaluation of the Concordance Mosaic Visualization

Shane Sheehan^*, Masood Masoodian, Saturnino Luz

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract / Description of output

Researchers working in areas such as lexicography, translation studies, and computational linguistics, use a combination of automated and semi-Automated tools to analyze the content of text corpora. Concordancing-or the arranging of passages of a textual corpus in alphabetical order according to user-defined keywords-is one of the oldest and still most widely used forms of text analysis. Concordance Mosaic is an interactive concordance visualization which emphasises quantitative information such as word frequency. While Concordance Mosaic is in active use by humanities scholars, no quantitative evaluation of the technique exists. In this paper, the Concordance Mosaic is quantitatively evaluated in comparison to a typical concordance browser. The comparison is evaluated using speed and accuracy on identified corpus analysis actions.

Original language	English
Title of host publication	Proceedings of the 26th International Conference Information Visualisation, IV 2022
Publisher	Institute of Electrical and Electronics Engineers
Pages	123-129
Number of pages	7
ISBN (Electronic)	9781665490078
DOIs	https://doi.org/10.1109/IV56949.2022.00028
Publication status	Published - 1 Jul 2022
Event	26th International Conference Information Visualisation, IV 2022 - Vienna, Austria Duration: 19 Jul 2022 → 22 Jul 2022

Publication series

Name	Proceedings of the International Conference on Information Visualisation
Volume	2022-July
ISSN (Print)	1093-9547

Conference

Conference	26th International Conference Information Visualisation, IV 2022
Country/Territory	Austria
City	Vienna
Period	19/07/22 → 22/07/22

Keywords / Materials (for Non-textual outputs)

document data visualization
quantitative evaluation
text visualization
visual knowledge discovery
Visualization in humanities

Access to Document

10.1109/IV56949.2022.00028

IV2022Accepted author manuscript, 460 KBLicence: Creative Commons: Attribution (CC-BY)

Cite this

Sheehan, S., Masoodian, M., & Luz, S. (2022). Task-based Quantitative Evaluation of the Concordance Mosaic Visualization. In Proceedings of the 26th International Conference Information Visualisation, IV 2022 (pp. 123-129). (Proceedings of the International Conference on Information Visualisation; Vol. 2022-July). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/IV56949.2022.00028

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title = "Task-based Quantitative Evaluation of the Concordance Mosaic Visualization",

abstract = "Researchers working in areas such as lexicography, translation studies, and computational linguistics, use a combination of automated and semi-Automated tools to analyze the content of text corpora. Concordancing-or the arranging of passages of a textual corpus in alphabetical order according to user-defined keywords-is one of the oldest and still most widely used forms of text analysis. Concordance Mosaic is an interactive concordance visualization which emphasises quantitative information such as word frequency. While Concordance Mosaic is in active use by humanities scholars, no quantitative evaluation of the technique exists. In this paper, the Concordance Mosaic is quantitatively evaluated in comparison to a typical concordance browser. The comparison is evaluated using speed and accuracy on identified corpus analysis actions.",

keywords = "document data visualization, quantitative evaluation, text visualization, visual knowledge discovery, Visualization in humanities",

author = "Shane Sheehan and Masood Masoodian and Saturnino Luz",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 26th International Conference Information Visualisation, IV 2022 ; Conference date: 19-07-2022 Through 22-07-2022",

year = "2022",

month = jul,

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doi = "10.1109/IV56949.2022.00028",

language = "English",

series = "Proceedings of the International Conference on Information Visualisation",

publisher = "Institute of Electrical and Electronics Engineers",

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booktitle = "Proceedings of the 26th International Conference Information Visualisation, IV 2022",

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}

Sheehan, S, Masoodian, M & Luz, S 2022, Task-based Quantitative Evaluation of the Concordance Mosaic Visualization. in Proceedings of the 26th International Conference Information Visualisation, IV 2022. Proceedings of the International Conference on Information Visualisation, vol. 2022-July, Institute of Electrical and Electronics Engineers, pp. 123-129, 26th International Conference Information Visualisation, IV 2022, Vienna, Austria, 19/07/22. https://doi.org/10.1109/IV56949.2022.00028

Task-based Quantitative Evaluation of the Concordance Mosaic Visualization. / Sheehan, Shane; Masoodian, Masood; Luz, Saturnino.
Proceedings of the 26th International Conference Information Visualisation, IV 2022. Institute of Electrical and Electronics Engineers, 2022. p. 123-129 (Proceedings of the International Conference on Information Visualisation; Vol. 2022-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Task-based Quantitative Evaluation of the Concordance Mosaic Visualization

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AU - Masoodian, Masood

AU - Luz, Saturnino

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N2 - Researchers working in areas such as lexicography, translation studies, and computational linguistics, use a combination of automated and semi-Automated tools to analyze the content of text corpora. Concordancing-or the arranging of passages of a textual corpus in alphabetical order according to user-defined keywords-is one of the oldest and still most widely used forms of text analysis. Concordance Mosaic is an interactive concordance visualization which emphasises quantitative information such as word frequency. While Concordance Mosaic is in active use by humanities scholars, no quantitative evaluation of the technique exists. In this paper, the Concordance Mosaic is quantitatively evaluated in comparison to a typical concordance browser. The comparison is evaluated using speed and accuracy on identified corpus analysis actions.

AB - Researchers working in areas such as lexicography, translation studies, and computational linguistics, use a combination of automated and semi-Automated tools to analyze the content of text corpora. Concordancing-or the arranging of passages of a textual corpus in alphabetical order according to user-defined keywords-is one of the oldest and still most widely used forms of text analysis. Concordance Mosaic is an interactive concordance visualization which emphasises quantitative information such as word frequency. While Concordance Mosaic is in active use by humanities scholars, no quantitative evaluation of the technique exists. In this paper, the Concordance Mosaic is quantitatively evaluated in comparison to a typical concordance browser. The comparison is evaluated using speed and accuracy on identified corpus analysis actions.

KW - document data visualization

KW - quantitative evaluation

KW - text visualization

KW - visual knowledge discovery

KW - Visualization in humanities

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M3 - Conference contribution

AN - SCOPUS:85147326123

T3 - Proceedings of the International Conference on Information Visualisation

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BT - Proceedings of the 26th International Conference Information Visualisation, IV 2022

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ER -

Sheehan S, Masoodian M, Luz S. Task-based Quantitative Evaluation of the Concordance Mosaic Visualization. In Proceedings of the 26th International Conference Information Visualisation, IV 2022. Institute of Electrical and Electronics Engineers. 2022. p. 123-129. (Proceedings of the International Conference on Information Visualisation). doi: 10.1109/IV56949.2022.00028

Task-based Quantitative Evaluation of the Concordance Mosaic Visualization

Abstract / Description of output

Publication series

Conference

Keywords / Materials (for Non-textual outputs)

Access to Document

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Cite this