Abstract
With more than one billion active users, Instagram is one of the most widely utilized social media platforms. Although recent research has begun to analyze brand-related images, Instagram remains largely neglected within halal food research. In this study, we aim to fill this research gap by collecting, labeling, aggregating, clustering, analyzing, and mapping halal food images, text, and social tagging on Instagram. In total, approximately 95,000 photos related to #halalfood tag were extracted from Instagram along with data related to photo captions, social tags, and comments on the posted photos. Google’s Cloud Vision Application Programming Interface (API) was employed for image labeling to represent context of the photos. The photos were categorized, based on their label, into food, place, advertisement, event, and unhealthy food. The captions and comments in each category were analyzed using the associate network and sentiment analysis approaches. The study found the most frequent tags in Instagram posts, besides the obvious halal food related tags, were #halalfoodexpo, #halalfoodkorea, #halalfoodfestival, and #burger. Furthermore, the most influential tags, besides the halal food related tags, were #halalfoodexpo, #chicken, #halalfoodkorea, #halaltourism, and #repost. In addition, it was found that most of the Instagram data contain positive sentiments towards halal food.
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Data availability
The datasets generated during and/or analysed during the current study are not publicly available due to privacy reasons but are available from the corresponding author on reasonable request.
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Funding
We would like to thank the UM Halal Research Centre staff for the administrative and technical support. This research was partly funded by Universiti Malaya, grant number BKS001-2019. The second author would like to thank Universiti Malaya for funding the postdoc position.
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Sulaiman, A., Feizollah, A., Mostafa, M.M. et al. Profiling the halal food consumer on Instagram: integrating image, textual, and social tagging data. Multimed Tools Appl 82, 10867–10886 (2023). https://doi.org/10.1007/s11042-022-13685-3
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DOI: https://doi.org/10.1007/s11042-022-13685-3