Predicting consumer personality traits in the sharing economy: The case of Airbnb

Murat Acar and Aysegul Toker

Applied Marketing Analytics: The Peer-Reviewed Journal, 2019, vol. 5, issue 1, 83-96

Abstract: For today’s human-centred engagement models and disruptive innovations, personalisation is paramount. In this regard, the use of Big Data analytics to leverage unstructured and user-generated content and create psychographic or psychologically-personalised marketing could well be a game-changer. This article describes a method to identify the ‘Big Five personalities’ of Airbnb guests through the linguistic analysis of their reviews. The study, conducted with IBM Watson Personality Insights AI, obtained these psychometric insights from a sample of 512 guests who had written at least 1,500 words’ worth of reviews. The statistically significant results indicate that Airbnb guests score high in altruism, cooperation, sympathy, trust, cautiousness, dutifulness, activity-level, extraversion, artistic interests, intellect, liberalism and openness. Concurrent with this, they score low in excitement-seeking, gregariousness, anger and self-consciousness.

Keywords: sharing economy; Big Data; artificial intelligence; user-generated content; content analysis; linguistic analytics; personality analysis (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:aza:ama000:y:2019:v:5:i:1:p:83-96

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