A Bayesian index of association: comparison with other measures and performance

The article discusses a Bayesian measure of association, B-index, and compares it with the other existing measures of agreement, association, and similarity, both chance-corrected and non-corrected: Scott’s π, Krippendorff’s α, Cohen’s κ, Bennett, Alpert & Goldstein’s S, Cosine similarity, and t...

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Published in:	Quality & quantity Vol. 58; no. 1; pp. 277 - 305
Main Author:	Oleinik, Anton
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.02.2024 Springer Springer Nature B.V
Subjects:	Algorithms Analysis Associations Bayesian analysis Computational linguistics Computer mediated communication Computer science Content analysis Indexes Information management Language processing Methodology of the Social Sciences Natural language interfaces Psychology Social Sciences Measures of inter-coder agreement Classification Measures of similarity PageRank Annotation Consensus Content analysis
ISSN:	0033-5177, 1573-7845
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Abstract	The article discusses a Bayesian measure of association, B-index, and compares it with the other existing measures of agreement, association, and similarity, both chance-corrected and non-corrected: Scott’s π, Krippendorff’s α, Cohen’s κ, Bennett, Alpert & Goldstein’s S, Cosine similarity, and the Jaccard similarity coefficient. PageRank adapted to particularities of annotation is also added to this list. Two versions of B-index are considered: with the informative and non-informative priors. An algorithm for calculating B-index written in pseudocode is provided. Particular attention is devoted to the uses of those measures in content analysis, communication studies, computational linguistics, psychology, computer science and network science. Real-world data gathered using an online platform for content analysis allowed comparing the behavior of all eight measures included in the scope of analysis. Three short texts (164 data points/sentences in total) were coded by 66 annotators. The behaviors of B-index with the non-informative prior and Bennett, Alpert & Goldstein’s S have some common patterns.
AbstractList	The article discusses a Bayesian measure of association, B-index, and compares it with the other existing measures of agreement, association, and similarity, both chance-corrected and non-corrected: Scott’s π, Krippendorff’s α, Cohen’s κ, Bennett, Alpert & Goldstein’s S, Cosine similarity, and the Jaccard similarity coefficient. PageRank adapted to particularities of annotation is also added to this list. Two versions of B-index are considered: with the informative and non-informative priors. An algorithm for calculating B-index written in pseudocode is provided. Particular attention is devoted to the uses of those measures in content analysis, communication studies, computational linguistics, psychology, computer science and network science. Real-world data gathered using an online platform for content analysis allowed comparing the behavior of all eight measures included in the scope of analysis. Three short texts (164 data points/sentences in total) were coded by 66 annotators. The behaviors of B-index with the non-informative prior and Bennett, Alpert & Goldstein’s S have some common patterns. The article discusses a Bayesian measure of association, B-index, and compares it with the other existing measures of agreement, association, and similarity, both chance-corrected and non-corrected: Scott's [pi], Krippendorff's [alpha], Cohen's [kappa], Bennett, Alpert & Goldstein's S, Cosine similarity, and the Jaccard similarity coefficient. PageRank adapted to particularities of annotation is also added to this list. Two versions of B-index are considered: with the informative and non-informative priors. An algorithm for calculating B-index written in pseudocode is provided. Particular attention is devoted to the uses of those measures in content analysis, communication studies, computational linguistics, psychology, computer science and network science. Real-world data gathered using an online platform for content analysis allowed comparing the behavior of all eight measures included in the scope of analysis. Three short texts (164 data points/sentences in total) were coded by 66 annotators. The behaviors of B-index with the non-informative prior and Bennett, Alpert & Goldstein's S have some common patterns.
Audience	Academic
Author	Oleinik, Anton
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SubjectTerms	Algorithms Analysis Associations Bayesian analysis Computational linguistics Computer mediated communication Computer science Content analysis Indexes Information management Language processing Methodology of the Social Sciences Natural language interfaces Psychology Social Sciences
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Title	A Bayesian index of association: comparison with other measures and performance
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