Mouse tracking IAT in customer research: an investigation of users’ implicit attitudes towards social networks

Monaro, Merylin, Negri, Paolo, Zecchinato, Francesca, Gamberini, Luciano and Sartori, Giuseppe (2021) Mouse tracking IAT in customer research: an investigation of users’ implicit attitudes towards social networks. Russo, D., Ahram, T., Karwowski, W., Di Bucchianico, G. and Tajar, R. (eds.) In Intelligent Human Systems Integration 2021. vol. 1322, Springer Cham. pp. 691-696 . (doi:10.1007/978-3-030-68017-6_102).

Abstract

The Implicit Association Test (IAT) has been widely used over the past as an implicit measure of cognition. In a recent attempt to better understand the mechanisms underlying the IAT, Yu et al. (2012) modified the classical IAT paradigm introducing a novel classification method based on mouse dynamics analyses (Mouse Tracking IAT; MT-IAT). The present study sought to empirically evaluate the feasibility of applying the MT-IAT to the consumer research field. Specifically, the analysis of mouse movements was applied to explore users’ implicit attitudes towards two popular social networks: Facebook and Twitter. Forty participants performed a MT-IAT task, where they were asked to classify Facebook/Twitter and positive/negative images. Results replicated the IAT effect, demonstrating that the mouse response time was significantly shorter in the compatible block as compared to the incompatible block. These findings successfully extended the implementation of the MT-IAT to a novel field of consumer research.

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Contributors

Author: Francesca Zecchinato

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