Global halal food discourse on social media: a text mining approach

Abstract

ABSTRACT No previous studies have explored the distinct role played by halal food discourse on social media. This study fills this research gap by investigating the structure, dynamics and sentiments related to halal food tweets using methods borrowed from text mining and social network analytics. Based on sample of 11,700 world-wide random tweets, we used both the NRC and the AFINN lexicons to gauge worldwide sentiments towards halal food. Although results show a generally positive sentiment, the tweets also reflect a general concern about animal welfare. Community detection techniques revealed a strong homophily effect among different halal food communities. This effect occurs when actors in an environment similar to a virtual room deal with topics of common interest or discuss common agenda. Our findings hold important implications for different stakeholders as they underscore the relational nature of halal food networks and the importance of the strategic management of social media as a critical communication tool.