Configurations of Causal Conditions Leading to Geotagged Image and Social Context Recognition in the Case of AI Media Platform

Adrian Micu, Alexandru Capatina, Angela-Eliza Micu, Robert Rusu and Constantin Avram
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Adrian Micu: Dunarea de Jos University of Galati, Romania
Alexandru Capatina: Dunarea de Jos University of Galati, Romania
Angela-Eliza Micu: Ovidius University of Constanta, Romania
Robert Rusu: Dunarea de Jos University of Galati, Romania
Constantin Avram: Dunarea de Jos University of Galati, Romania

Risk in Contemporary Economy, 2019, 479-486

Abstract: The increasing use of geotagged image and social context recognition in Social Media Marketing offer companies that are looking for using emerging AI Media solutions opportunities to post relevant content on each social network in order to drive the maximum engagement with their audience. This research aims to identify and further analyze the feedback of potential users of an AI-based platform for Social Media Marketing, regarding its capabilities focused on geotagged image and social context recognition. Through this hybrid quantitative-qualitative approach, marketing professionals from FutureWeb research team propose different causal configurations of forthcoming capabilities of the AI-based platform. Gaining visibility through brand related photo or video geotagged on social media; free advertising through tagging a location while people add an image containing a brand’s logo; incentives given to geotagged images uploaded on social networks; richer behavioural data provided by geotagged image recognition features and capitalizing on location-based image recognition to predict consumer behaviour and improve services are analysed as antecedents of intention to test AI Media platform.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ddj:fserec:y:2019:p:479-486

DOI: 10.35219/rce2067053255

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