Variations in power of opinion leaders in online communication networks

Adalat, Mohsin; Niazi, Muaz A.; Vasilakos, Athanasios V.

doi:10.1098/rsos.180642

Cited by 12 publications

(12 citation statements)

References 54 publications

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“…This is a methodology recently described for the integration of ranked genes across different prioritization tools (Cruz-Monteaqudo et al., 2016; López-Cortés et al., 2018; Tejera et al., 2017), but this constitutes the first report of application and validity in studies related to social sciences. The idea of normalizing to explore a ranked node centrality had also being recently explored in communication networks but not as a direct comparison measure across networks (Adalat et al., 2018). Moreover our results in factorial analysis showed that normalized centralities are very well correlated between networks; it is a property of centrality indexes already identified in Valente et al.…”

Section: Discussionmentioning

confidence: 99%

Analysis of organizational power networks through a holistic approach using consensus strategies

Rámos

Franco-Crespo

González-Pérez

et al. 2019

Heliyon

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Power is one of the most complex organizational attributes to understand due to the multiple related variables and dimensions in which it appears. The ownership and use and of power are reflected in the interpersonal relationships within an organization, as a result, modeling its structure and interactions can lead to knowledge about the power networks that shape it. The objective of this study was to identify the behavior of organizational networks based on existing sources of power, using a consensual analysis of the different topologies present in these networks. The study was carried out in a private production company in Ecuador, which has representation at a domestic level. To this end, a 12-question personalized questionnaire was designed with the aim of identifying specific networks and was applied to 1190 workers in the company. The results were obtained using organizational network analysis and a consensus strategy to integrate the centralities found in multiple networks into one. This study can serve as a reference to organizations, so they can know the relationships between people within it, as part of their management process. In this way, the identification of people within power networks is useful for knowing the “key” actors in the promotion of organizational changes, as well as for the development of career plans based on the position that people occupy in the organizational system.

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Section: Discussionmentioning

confidence: 99%

Analysis of organizational power networks through a holistic approach using consensus strategies

Rámos

Franco-Crespo

González-Pérez

et al. 2019

Heliyon

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“…Feng [ 20 ] introduced five types of central users including conversation starter, influencer, active engager, network builder, and information bridge. Among them, conversation starters who have a significant number of indegree links but a few or none outdegree links, and influencers who have numerous indegree links with a few outdegree links, are considered to be opinion leaders and information sources in long-term discussions on Twitter [ 21 ].…”

Section: Related Workmentioning

confidence: 99%

“…Such users can be effectively identified by using the outdegree metric. An empirical study conducted in [ 21 ] showed that the users with high indegree can be considered to be opinion leaders in long-time discussions. In [ 30 ], the authors used weighted indegree to identify the influential nodes of the network of people tweeting.…”

Section: Proposed Approachmentioning

confidence: 99%

Understanding Malicious Accounts in Online Political Discussions: A Multilayer Network Approach

Nguyen

Wang

Dai

et al. 2021

Sensors

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Online social media platforms play an important role in political communication where users can freely express and exchange their political opinion. Political entities have leveraged social media platforms as essential channels to disseminate information, interact with voters, and even influence public opinion. For this purpose, some organizations may create one or more accounts to join online political discussions. Using these accounts, they could promote candidates and attack competitors. To avoid such misleading speeches and improve the transparency of the online society, spotting such malicious accounts and understanding their behaviors are crucial issues. In this paper, we aim to use network-based analysis to sense influential human-operated malicious accounts who attempt to manipulate public opinion on political discussion forums. To this end, we collected the election-related articles and malicious accounts from the prominent Taiwan discussion forum spanning from 25 May 2018 to 11 January 2020 (the election day). We modeled the discussion network as a multilayer network and used various centrality measures to sense influential malicious accounts not only in a single-layer but also across different layers of the network. Moreover, community analysis was performed to discover prominent communities and their characteristics for each layer of the network. The results demonstrate that our proposed method can successfully identify several influential malicious accounts and prominent communities with apparent behavior differences from others.

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“…First, the conversation starter is identified using the statistical analysis of edge weight, which showed the network ranking of the top connected Twitter users. They are indicated with the high value of edge weight, high value on the "in-degree" links, and only a few the "out-degree" links, and the high number of impressions [18]. The posts from these users are tweeted, replied to, and retweeted by most of the accounts that using "COVID19Indonesia," "Inpres," and "Pemerintah" words.…”

Section: ) Conversation Startermentioning

confidence: 99%

Mapping the Social Movement Pattern During COVID-19 Outbreaks with the Twitter Metadata by Using Social Network Analysis (SNA) Method

Bahri¹,

Hakim²,

Sucipto³

2021

Proceedings of the 1st International Conference on Law and Human Rights 2020 (ICLHR 2020)

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The National positivity rates reached 14,1 percent in September 2020. More than 4000 cases were confirmed in a day, pushing the government to implement a strict policy that potentially creates pros and cons and may trigger social movement in the affected society. In the theoretical framework, the social movement started in four main stages: emergence, coalescence, bureaucratization, and decline. The polarization of the movement is usually started by the grassroots actors towards a common interest. This research aimed to analyze the social movement's pattern and characteristics in the digital sphere by using the Social Network Analysis (SNA) method. It particularly seeks to understand the conversation network and involved actors by analyzing the Twitter dataset containing 36,929 tweets, with "COVID19Indonesia," "Inpres" and "Pemerintah" words, obtained from July to September 2020. The RStudio Tools used to conduct sentiment analysis to gather people's responses to the COVID-19 related policy, and Gephi Mapping Software to identify the conversation pattern between related actors. The research findings are that government-related accounts can be identified as a conversation starter. A key-person like @Fadlizon can be identified as an influencer. The mainstream media can be identified as active engagement, while ordinary people can be identified as the network builder. The conversation networks, which the government and mainstream media led, successfully triggered a social movement to support a positive public opinion about the Government Policy to Fight COVID-19 Pandemic. The sentiment analysis concluded that 65 percent responded positively, 18 percent neutral, and only 10 percent responded negatively to the government policy during the COVID-19 pandemic. The findings show the opposite aspects compared to the social movement theory. Firstly, the key actors and movement polar are dominated by the government-related and mainstream mass media to support the government policy itself, not from the grassroots actors. Secondly, Involved actors are borderless, who came from many different backgrounds and separate into a smaller conversation network to support common goals. However, the main social movement pattern is still relevant to the main stage. It started with emergence, coalescence, bureaucratization and ended with a decline stage. The new phenomenon discovered is that the digital social movement is coming from the people against the government policy or the government to influence public opinion.

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Variations in power of opinion leaders in online communication networks

Cited by 12 publications

References 54 publications

Analysis of organizational power networks through a holistic approach using consensus strategies

Analysis of organizational power networks through a holistic approach using consensus strategies

Understanding Malicious Accounts in Online Political Discussions: A Multilayer Network Approach

Mapping the Social Movement Pattern During COVID-19 Outbreaks with the Twitter Metadata by Using Social Network Analysis (SNA) Method

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