Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties

Rahman, Md. Habibur; Prama, Tabia Tanzin; Anwar, Musfique

doi:10.1007/978-3-030-73050-5_57

Hybrid Intelligent Systems

2021

DOI: 10.1007/978-3-030-73050-5_57

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Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties

Md. Habibur Rahman

Tabia Tanzin Prama

Musfique Anwar

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2023

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Identification of Influential Users in Online Social Network: A Brief Overview

Ferdous¹,

Anwar²

2023

JCC

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Information networks where users join a network, publish their own content, and create links to other users are called Online Social Networks (OSNs). Nowadays, OSNs have become one of the major platforms to promote both new and viral applications as well as disseminate information. Social network analysis is the study of these information networks that leads to uncovering patterns of interaction among the entities. In this regard, finding influential users in OSNs is very important as they play a key role in the success above phenomena. Various approaches exist to detect influential users in OSNs, starting from simply counting the immediate neighbors to more complex machine-learning and message-passing techniques. In this paper, we review the recent existing research works that focused on identifying influential users in OSNs.

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Identification of Influential Users in Online Social Network: A Brief Overview

Ferdous¹,

Anwar²

2023

JCC

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show abstract

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Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties

Cited by 1 publication

References 14 publications

Identification of Influential Users in Online Social Network: A Brief Overview

Identification of Influential Users in Online Social Network: A Brief Overview

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