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Detection of seed users vis-à-vis social synchrony in online social networks using graph analysis

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Abstract

The dominance and prevalence of social media in the present world are significant because the role supplied by social networks is gradually growing with the passage of time. These social networks are often complicated networks in which each user is designated by a node and interactions between two users are symbolized by edges. People often express their opinions on any event via social media platforms. The interaction between users at a specific event, such as COVID-19, may constitute social synchrony, defined as a large population of users performing a specific action in unison. Identifying the seed users (influential users) from that event can be vital for a range of applications. Therefore, the current study proposes a framework to identify the seed users that works on the principles of graph analysis, viz. clustering, transitivity, and network centrality. Extensive experimentation is carried out using a self-collected dataset of COVID-19 tweets. Our dataset shows encouraging results in finding seed users in complicated networks.

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Data availability

Dataset will be made available on reasonable requests.

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Authors and Affiliations

  1. Amity Institute of Information Technology, Amity University, Noida, Uttar Pradesh, 201313, India

    Shabana Nargis Rasool & Sarika Jain

  2. Islamic University of Science and Technology, Awantipora, Jammu & Kashmir, 192122, India

    Ayaz Hassan Moon

Authors
  1. Shabana Nargis Rasool
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  2. Sarika Jain
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  3. Ayaz Hassan Moon
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Correspondence to Shabana Nargis Rasool.

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The authors declare that they have no competing interests of a financial or personal nature that could influence this study or its interpretation.

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Rasool, S.N., Jain, S. & Moon, A.H. Detection of seed users vis-à-vis social synchrony in online social networks using graph analysis. Int. j. inf. tecnol. 15, 3715–3726 (2023). https://doi.org/10.1007/s41870-023-01435-z

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  • DOI: https://doi.org/10.1007/s41870-023-01435-z

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