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Article Dans Une Revue IEEE Access Année : 2021

Dataset of coronavirus content from Instagram with an exploratory analysis

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The novel coronavirus (COVID-19) pandemic outbreak is drastically shaping and reshaping many aspects of our life, with a huge impact on our social life. In this era of lockdown policies in most of the major cities around the world, we see a huge increase in people and professionals’ engagement in social media. Online Social Networks are playing an important role in news propagation as well as keeping people in contact. At the same time, social media is both a blessing and a curse as the coronavirus infodemic has become a major concern, and is already a topic that needs special attention and further research. In this study, we publish a multilingual coronavirus (COVID-19) Instagram dataset that we have continuously collected during the first wave of the pandemic from 5 January 2020 to 30 May 2020. The dataset contains 25.7K posts, 829K comments, and 3.2M likes in various subjects from different publishers such as ‘public accounts’, ‘fake accounts (bots)’, ‘newsagencies’, ‘influencers’, ‘celebrities’, ‘business pages’, etc. In addition to the dataset, this paper provides an analysis of the behaviour of the publishers. We study the behavioural aspects of the users in terms of their engagement, use of hashtags, activities, reactions as well as a full analysis of the published content related to the COVID-19. We believe this contribution helps the research community to better understand the dynamics behind this phenomenon in Instagram, as one of the major social media.
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hal-03559489 , version 1 (27-02-2024)

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Koosha Zarei, Reza Farahbakhsh, Noel Crespi, Gareth Tyson. Dataset of coronavirus content from Instagram with an exploratory analysis. IEEE Access, 2021, 9, pp.157192-157202. ⟨10.1109/ACCESS.2021.3126552⟩. ⟨hal-03559489⟩
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