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What People Post During the Movement Control Order (MCO): A Content Analysis of Intagram’s Top Posts

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Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems (ICETIS 2022)

Abstract

The outbreak of the COVID-19 pandemic in the year 2020 led the government of Malaysia to impose the Movement Control Order (MCO) to limit the spread of the virus, which resulted in people becoming heavily reliant on social media as a means of communication and expression of thought. Analysing the trends and sentiments of popular content posted on social media can provide insight into the market for marketers to plan and execute their social media strategies and marketing communication campaigns. Using qualitative content analysis (QCA), this research aims to identify the overall image content and caption sentiments reflected in the top Instagram posts posted during the first MCO, from the middle of March to June of the year 2020. A total of 200 posts were collected on Instagram and were filtered with the hashtags ‘#mco’ and ‘#cmco’. The content of the posts was categorised into food, gadgets, captioned photos, pets, activities, selfies, fashion, landscapes, portraits, and videos; while the sentiments of the posts were categorised into narratives of fear, fun, sadness, responsibility, and encouragement. The results show that portraits and narratives of fun were dominant during the first MCO, suggesting that positive and portrait-centric posts on social media are preferred over other types during a crisis, which might provide valuable insight for businesses to design their social media strategies.

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Correspondence to Way Zhe Yap .

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Goh, H.L., Foo, W.H., Cham, T.H., Sia, B.C., Yap, W.Z. (2023). What People Post During the Movement Control Order (MCO): A Content Analysis of Intagram’s Top Posts. In: Al-Sharafi, M.A., Al-Emran, M., Al-Kabi, M.N., Shaalan, K. (eds) Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems . ICETIS 2022. Lecture Notes in Networks and Systems, vol 573. Springer, Cham. https://doi.org/10.1007/978-3-031-20429-6_9

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