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Using Deep Learning to Investigate Digital Behavior in Culinary Tourism by Md Rajibul Hasan; Assem Abdunurova; Wenwen Wang; Jiawei Zheng; S.M. Riad Shams is a Social Sciences article available to read on EtoBox.

What is Using Deep Learning to Investigate Digital Behavior in Culinary Tourism about?

## Purpose The purpose of this study is to gather insights into digital consumer behaviour related to Chinese restaurents by examining visual contents on Tripadvisor platform. ## Design/methodology/approach Using the deep learning approach, this research assessed consumer-posted online content of dining experiences by implementing image analysis and clustering. Text mining using word cloud analysis revealed the most frequently repeated keywords. ## Findings First, 4,000 photos of nine Chinese restaurants posted on Tripadvisor’s website were analyzed using image recognition via Inception V3 and Google’s deep learning network; this revealed 12 hierarchical image clusters. Then, an open-questionnaire survey of 125 Chinese respondents investigated consumers’ information needs before visiting a restaurant and after purchasing behavior (motives to share). ## Practical implications This study contributes to culinary marketing development by introducing a new analysis methodology and demonstrating its application by exploring a wide range of keywords and visual images published on the internet. ## Originality/value This research extends and contributes to the literature regarding visual us

Who reads Using Deep Learning to Investigate Digital Behavior in Culinary Tourism?

Author

Md Rajibul Hasan; Assem Abdunurova; Wenwen Wang; Jiawei Zheng; S.M. Riad Shams

Publisher

Emerald

Published

2020

Language

EN

Field

Social Sciences