Using Social Network Analysis to Understand Public Discussions: The Case Study of #SaudiWomenCanDrive on Twitter

Jastania, Zubaida; Ahtisham, Mohammad; Ayaz, Rabeeh; Saeedi, Kawther

doi:10.14569/ijacsa.2020.0110230

Cited by 3 publications

(2 citation statements)

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“…The identification of the cohesive groups of people in the discussion is an extension to our previous work [47], where identification of the critical people in a discussion is studied.…”

Section: A Cohesive Groups Identificationmentioning

confidence: 99%

“…We use the value of p=0.85 for PageRank, as widely used in the literature. Within the course of the investigation, the initial information set is converted into four networks: Mention-Network, Co-Mention-Network, Hashtag-Network, and Retweet-Network, interested readers can find the minutiae in our earlier work [47]. The substance of these networks complies involving network science for succeeding analysis and formulation.…”

Section: B Network Extractionmentioning

confidence: 99%

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Analyzing Public Discussions About #SaudiWomenCanDrive Using Network Science

et al. 2022

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“…The identification of the cohesive groups of people in the discussion is an extension to our previous work [47], where identification of the critical people in a discussion is studied.…”

Section: A Cohesive Groups Identificationmentioning

confidence: 99%

Section: B Network Extractionmentioning

confidence: 99%

Analyzing Public Discussions About #SaudiWomenCanDrive Using Network Science

et al. 2022

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Detecting Trending Event Topics Using Sentiment Driven Derivatives Method on Twitter

Tijare¹,

Rani²

2021

INDJCSE

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A Social Network Analysis: Identifying Influencers in The COVID-19 Vaccination Discussion on Twitter

Habibi

Cahyo

2021

Compiler

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Social media analytics, especially Twitter, has experienced significant growth over the last few years. The data generated by Twitter provides valuable information to many stakeholders regarding user behavior, preferences, tastes, and characteristics. The presence of influencers on social media can invite interaction with other users. An influencer can affect the speed of spreading information on social media. This study looks at the influence of influencers and information dissemination channels on Twitter data related to COVID-19 vaccination in Indonesia as one of the hot Twitter discussion trends. This study applies Social Network Analysis (SNA) as a theoretical and methodological framework to show that interactions between users have differences on the network when the analyzed tweets are divided into mention and retweet networks. This study found that the key accounts in disseminating information related to Covid-19 vaccination were dominated by official accounts of government organizations and online news portals. The official Twitter account of government organizations turns out to have an essential role in disseminating information related to COVID-19 vaccination, namely the @KemenkesRI account belonging to the Ministry of Health of the Republic of Indonesia and the @Puspen_TNI account belonging to the TNI Information Center.

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Using Social Network Analysis to Understand Public Discussions: The Case Study of #SaudiWomenCanDrive on Twitter

Cited by 3 publications

References 0 publications

Analyzing Public Discussions About #SaudiWomenCanDrive Using Network Science

Analyzing Public Discussions About #SaudiWomenCanDrive Using Network Science

Detecting Trending Event Topics Using Sentiment Driven Derivatives Method on Twitter

A Social Network Analysis: Identifying Influencers in The COVID-19 Vaccination Discussion on Twitter

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