Identification of key opinion leaders in healthcare domain using weighted Social Network Analysis

2016 ◽  
Author(s):  
Mayur R. Gotecha ◽  
Manasi S. Patwardhan
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Opinion Leaders ◽  
Key Opinion Leaders

scholarly journals Using Social Network Analysis and Social Capital to Identify User Roles on Polarized Political Conversations on Twitter

2019 ◽  
Vol 5 (2) ◽  
pp. 205630511984874 ◽  
Author(s):  
Raquel Recuero ◽  
Gabriela Zago ◽  
Felipe Soares
Keyword(s):  
Social Capital ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Opinion Leaders ◽  
Information Flows ◽  
Network Metrics ◽  
Network Analysis Metrics

In this article, we discuss the roles users play in political conversations on Twitter. Our case study is based on data collected in three dates during the former Brazilian president Lula’s corruption trial. We used a combination of social network analysis metrics and social capital to identify the users’ roles during polarized discussions that took place in each of the dates analyzed. Our research identified four roles, each associated with different aspects of social capital and social network metrics: activists, news clippers, opinion leaders, and information influencers. These roles are particularly useful to understand how users’ actions on political conversations may influence the structure of information flows.

scholarly journals Identifying student opinion leaders to lead e-cigarette interventions: protocol for a randomized controlled pragmatic trial

Trials ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kar-Hai Chu ◽  
Sara Matheny ◽  
Alexa Furek ◽  
Jaime Sidani ◽  
Susan Radio ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Pragmatic Trial ◽  
Opinion Leader ◽  
Opinion Leaders ◽  
Student Opinion ◽  
Randomized Controlled ◽  
School Based ◽  
Peer Leader

Abstract Background After the US Surgeon General declared youth electronic cigarette (e-cigarette) use an epidemic in 2018, the number of youth e-cigarette users continued to surge, growing from 3.8 million in 2018 to over 5 million 2019. Youth who use e-cigarettes are at a substantially higher risk of transitioning to traditional cigarettes, becoming regular cigarette smokers, and increasing their risk of developing tobacco-related cancer. A majority of youth are misinformed about e-cigarettes, often believing they are not harmful or contain no nicotine. Middle school students using e-cigarettes have been affected by its normalization leading to influence by their peers. However, social and group dynamics can be leveraged for a school-based peer-led intervention to identify and recruit student leaders to be anti-e-cigarette champions to prevent e-cigarette initiation. This study outlines a project to use social network analysis to identify student opinion-leaders in schools and train them to conduct anti-e-cigarette programming to their peers. Methods In the 2019–2020 academic school year, 6th grade students from nine schools in the Pittsburgh area were recruited. A randomized controlled trial (RCT) was conducted with three arms—expert, elected peer-leader, and random peer-leader—for e-cigarette programming. Sixth grade students in each school completed a network survey that assessed the friendship networks in each class. Students also completed pre-intervention and post-intervention surveys about their intention-to-use, knowledge, and attitudes towards e-cigarettes. Within each peer-led arm, social network analysis was conducted to identify peer-nominated opinion leaders. An e-cigarette prevention program was administered by (1) an adult content-expert, (2) a peer-nominated opinion leader to assigned students, or (3) a peer-nominated opinion leader to random students. Discussion This study is the first to evaluate the feasibility of leveraging social network analysis to identify 6th grade opinion leaders to lead a school-based e-cigarette intervention. Trial registration ClinicalTrials.gov NCT04083469. Registered on September 10, 2019.

scholarly journals Identification of Key Opinion Leaders in Pharmaceutics Using Network Analysis

2021 ◽  
pp. 01-05
Author(s):  
Prof. Anuja Phapale ◽  
Sarthak Kulkarni ◽  
Pritam Bagad ◽  
Hrishikesh Joshi ◽  
Himanshu Randad
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Life Science ◽  
Opinion Leader ◽  
Opinion Leaders ◽  
Centrality Measures ◽  
Pubmed Central ◽  
Key Opinion Leaders ◽  
Key Opinion Leader ◽  
The Web

The term Key Opinion Leader in marketing is not new. Key Opinion Leaders (KOLs) commonly known as thought leaders who play a crucial role in the life science industry. We through this project intend to implement the concept of identifying key opinion leaders using weighted Social Network Analysis (SNA). We intend to use European PubMed Central dataset for creating a weighted social Network of authors who have healthcare and medicine related publications and apply different centrality measures on it. In order to collect the data, we will be using one of the web scraping methods and predefined libraries like scrapy. After fetching and processing the data we intend to form a network of authors using python’s NetworkX library. This network will then be subjected to various centrality measures which in turn will give prominent opinion leaders as the output.

Use of Social Network Analysis to Identify Popular Opinion Leaders for a Youth-Led Sexual Violence Prevention Initiative

2021 ◽  
pp. 107780122199490
Author(s):  
Katie M. Edwards ◽  
Victoria L. Banyard ◽  
Emily A. Waterman ◽  
Skyler L. Hopfauf ◽  
Hee-Sung Shin ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Violence Prevention ◽  
Sexual Violence ◽  
Lessons Learned ◽  
Opinion Leaders ◽  
Participation Rates ◽  
Popular Opinion ◽  
Current Article

In the current article, we describe an innovative sexual violence (SV) prevention initiative that used social network analysis to identify youth and adult popular opinion leaders who were subsequently trained in best practices in SV prevention (e.g., bystander intervention) at a kickoff event (i.e., camp) of the initiative. We provide information on recruitment strategies, participation rates and how those rates varied by some demographic factors, reasons for nonattendance, the initial impact of the camp, and lessons learned. Despite challenges with youth and adult engagement, this innovative approach has the potential to transform the way we approach SV prevention among youth.

scholarly journals Applying social network analysis, centrality measures in identification of climate change adaptation opinion leaders

2016 ◽  
Vol 6 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Othieno Joseph ◽  
Mugivane I Fred ◽  
Nyaga Philip ◽  
Ogara William ◽  
Muchemi Gerald
Keyword(s):  
Climate Change ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Flow ◽  
Critical Role ◽  
Opinion Leaders ◽  
Centrality Measures ◽  
Agricultural Technologies ◽  
Change Communication

Climate change is negatively affecting livelihoods dependent on rain fed agriculture in Kenya. Adaptation through adoption of appropriate agricultural technologies is necessary. Communication plays a critical role in dissemination of climate change information and adaptation. The study applied social network analysis (SNA) using NodeXL computer programme to generate socio-grams that showed patterns of information flow from which important network and individual characteristic of the opinion leaders were described. This study shows that SNA is applicable in climate change communication to identify opinion leaders by mapping out information flow patterns and using measures of centrality.Int. J. Agril. Res. Innov. & Tech. 6 (1): 1-7, June, 2016

Hot Issues Detection on Weibo Based on Social Network Analysis

2013 ◽  
Vol 846-847 ◽  
pp. 1818-1825
Author(s):  
Xu Yao ◽  
Yu Yang ◽  
Yi Jing Fu ◽  
Yu Lin Li ◽  
Guo Shi Wu
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Detection ◽  
Event Detection ◽  
Opinion Leaders ◽  
Social Changes ◽  
Network Building ◽  
Innovative Model ◽  
Three Stages

Weibo is a leading twitter-like microblog service in China, acting as the key barometer of social changes. This paper proposes an innovative model, which automatically detects hot issues on Weibo based on social network analysis instead of search-based approaches. Three stages are consecutively collaborated to discover the hot issues and each issue was presented by a group of distinguished keywords as outcome of the model, i.e., firstly self-revised opinion leaders list construction, secondly keywords selection according to a weighting criterion, and finally keyword co-occurrence network building and event detection through community detection on the network.

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