Quantifying the effect of meaning variation in survey analysis

Henri Sintonen; Juha Raitio; Timo Honkela

doi:10.1007/978-3-319-11179-7_95

Quantifying the effect of meaning variation in survey analysis

Henri Sintonen, Juha Raitio, Timo Honkela

University of Helsinki

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

1 Citation (Scopus)

Abstract

Surveys are widely conducted as a means to obtain information on thoughts, opinions and feelings of people. The representativeness of a sample is a major concern in using surveys. In this article, we consider meaning variation which is another potentially remarkable but less studied source of problems. We use Grounded Intersubjective Concept Analysis (GICA) method to quantify meaning variation and demonstrate the effect on survey analysis through a case study in which food prices and food concepts are considered.

Original language	English
Title of host publication	Artificial Neural Networks and Machine Learning, ICANN 2014 - 24th International Conference on Artificial Neural Networks, Proceedings
Editors	Stefan Wermter, Cornelius Weber, Wlodzislav Duch, Timo Honkela, Petia Koprinkova-Hristova, Sven Magg, Günther Palm, Alessandro E. P. Villa
Publisher	Springer
Pages	757-764
Number of pages	8
ISBN (Electronic)	978-3-319-11179-7
ISBN (Print)	9783319111780
DOIs	https://doi.org/10.1007/978-3-319-11179-7_95
Publication status	Published - 2014
MoE publication type	A4 Conference publication
Event	International Conference on Artificial Neural Networks - Hamburg, Germany Duration: 15 Sept 2014 → 19 Sept 2014 Conference number: 24

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	8681 LNCS
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	International Conference on Artificial Neural Networks
Abbreviated title	ICANN
Country/Territory	Germany
City	Hamburg
Period	15/09/2014 → 19/09/2014

Keywords

computational epistemology
conceptual spaces
meaning variation
questionnaire data
Survey analysis

Access to Document

10.1007/978-3-319-11179-7_95

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Sintonen, H., Raitio, J., & Honkela, T. (2014). Quantifying the effect of meaning variation in survey analysis. In S. Wermter, C. Weber, W. Duch, T. Honkela, P. Koprinkova-Hristova, S. Magg, G. Palm, & A. E. P. Villa (Eds.), Artificial Neural Networks and Machine Learning, ICANN 2014 - 24th International Conference on Artificial Neural Networks, Proceedings (pp. 757-764). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8681 LNCS). Springer. https://doi.org/10.1007/978-3-319-11179-7_95

Sintonen, Henri ; Raitio, Juha ; Honkela, Timo. / Quantifying the effect of meaning variation in survey analysis. Artificial Neural Networks and Machine Learning, ICANN 2014 - 24th International Conference on Artificial Neural Networks, Proceedings. editor / Stefan Wermter ; Cornelius Weber ; Wlodzislav Duch ; Timo Honkela ; Petia Koprinkova-Hristova ; Sven Magg ; Günther Palm ; Alessandro E. P. Villa. Springer, 2014. pp. 757-764 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Sintonen, H, Raitio, J & Honkela, T 2014, Quantifying the effect of meaning variation in survey analysis. in S Wermter, C Weber, W Duch, T Honkela, P Koprinkova-Hristova, S Magg, G Palm & AEP Villa (eds), Artificial Neural Networks and Machine Learning, ICANN 2014 - 24th International Conference on Artificial Neural Networks, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8681 LNCS, Springer, pp. 757-764, International Conference on Artificial Neural Networks, Hamburg, Germany, 15/09/2014. https://doi.org/10.1007/978-3-319-11179-7_95

Quantifying the effect of meaning variation in survey analysis. / Sintonen, Henri; Raitio, Juha; Honkela, Timo.
Artificial Neural Networks and Machine Learning, ICANN 2014 - 24th International Conference on Artificial Neural Networks, Proceedings. ed. / Stefan Wermter; Cornelius Weber; Wlodzislav Duch; Timo Honkela; Petia Koprinkova-Hristova; Sven Magg; Günther Palm; Alessandro E. P. Villa. Springer, 2014. p. 757-764 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8681 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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Sintonen H, Raitio J, Honkela T. Quantifying the effect of meaning variation in survey analysis. In Wermter S, Weber C, Duch W, Honkela T, Koprinkova-Hristova P, Magg S, Palm G, Villa AEP, editors, Artificial Neural Networks and Machine Learning, ICANN 2014 - 24th International Conference on Artificial Neural Networks, Proceedings. Springer. 2014. p. 757-764. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-11179-7_95

Quantifying the effect of meaning variation in survey analysis

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