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dc.contributor.authorGuimaraes, Marcus
dc.contributor.authorAdamatti, Diana F.
dc.contributor.authorEmmendorfer, Leonardo
dc.date.accessioned2018-09-21T08:36:06Z
dc.date.available2018-09-21T08:36:06Z
dc.date.issued2018-02-23
dc.identifier.citationADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 7 (2018)
dc.identifier.issn2255-2863
dc.identifier.urihttp://hdl.handle.net/10366/138393
dc.description.abstractIn this paper, it is presented a mathematical modeling for the action line, or threshold line, of the Fogg Behavior Model (FBM) as well as an analysis of its positioning in relation to the dataset. According to the mathematical modeling formation process for both Motivation and Ability axes, the action line evaluation was performed by simulations via agents. This behavioral model is mainly used as an empirical evaluation method applied to processes based on persuasive technologies. The results showed that the threshold line should not be fixed, as originally proposed in the model, but dynamically allocated based on the Kolmogorov mean. This dynamic allocation ensures its use as a visual feature towards greater efficiency in triggers implementations. This work aims to contribute with an approach that transits between theoretical and practical when related to applications that requires the FBM, thus allowing the use of this behavioral model with higher degree of certainty and thus maximizing efficiency in the evaluation and implementation processes based on persuasive technologies.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherEdiciones Universidad de Salamanca (España)
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subjectComputación
dc.subjectInformótica
dc.subjectComputing
dc.subjectInformation Technology
dc.titleAn Agent-based Environment for Dynamic Positioning of the Fogg Behavior Model Threshold Line
dc.typeinfo:eu-repo/semantics/article
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess


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Attribution-NonCommercial-NoDerivs 3.0 Unported
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Unported