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Emergence of opinion leaders in reference networks.

ABSTRACT: Individuals often refer to opinions of others when they make decisions in the real world. Our question is how the people's reference structure self-organizes when people try to provide correct answers by referring to more accurate agents. We constructed an adaptive network model, in which each node represents an agent and each directed link represents a reference. In every iteration round within our model, each agent makes a decision sequentially by following the majority of the reference partners' opinions and rewires a reference link to a partner if the partner's performance falls below a given threshold. The value of this threshold is common for all agents and represents the performance assessment severity of the population. We found that the reference network self-organizes into a heterogeneous one with a nearly exponential in-degree (the number of followers) distribution, where reference links concentrate around agents with high intrinsic ability. In this heterogeneous network, the decision-making accuracy of agents improved on average. However, the proportion of agents who provided correct answers showed strong temporal fluctuation compared to that observed in the case in which each agent refers to randomly selected agents. We also found a counterintuitive phenomenon in which reference links concentrate more around high-ability agents and the population became smarter on average when the rewiring threshold was set lower than when it was set higher.

SUBMITTER: Ito MI

PROVIDER: S-EPMC5868794 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Emergence of opinion leaders in reference networks.

Ito Mariko I MI Ohtsuki Hisashi H Sasaki Akira A

PloS one 20180326 3

Individuals often refer to opinions of others when they make decisions in the real world. Our question is how the people's reference structure self-organizes when people try to provide correct answers by referring to more accurate agents. We constructed an adaptive network model, in which each node represents an agent and each directed link represents a reference. In every iteration round within our model, each agent makes a decision sequentially by following the majority of the reference partne ...[more]

PMID: 29579053

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Project description:BackgroundRapid identification of subject experts for medical topics helps in improving the implementation of discoveries by speeding the time to market drugs and aiding in clinical trial recruitment, etc. Identifying such people who influence opinion through social network analysis is gaining prominence. In this work, we explore how to combine named entity recognition from unstructured news articles with social network analysis to discover opinion leaders for a given medical topic.MethodsWe employed a Conditional Random Field algorithm to extract three categories of entities from health-related new articles: Person, Organization and Location. We used the latter two to disambiguate polysemy and synonymy for the person names, used simple rules to identify the subject experts, and then applied social network analysis techniques to discover the opinion leaders among them based on their media presence. A network was created by linking each pair of subject experts who are mentioned together in an article. The social network analysis metrics (including centrality metrics such as Betweenness, Closeness, Degree and Eigenvector) are used for ranking the subject experts based on their power in information flow.ResultsWe extracted 734,204 person mentions from 147,528 news articles related to obesity from January 1, 2007 through July 22, 2010. Of these, 147,879 mentions have been marked as subject experts. The F-score of extracting person names is 88.5%. More than 80% of the subject experts who rank among top 20 in at least one of the metrics could be considered as opinion leaders in obesity.ConclusionThe analysis of the network of subject experts with media presence revealed that an opinion leader might have fewer mentions in the news articles, but a high network centrality measure and vice-versa. Betweenness, Closeness and Degree centrality measures were shown to supplement frequency counts in the task of finding subject experts. Further, opinion leaders missed in scientific publication network analysis could be retrieved from news articles.

Project description:Background The ever-increasing burden of diabetes and the limited resources highlight the need for prioritization of national action goals for diabetes management. The Israeli National Diabetes Council (INDC) initiated a prioritization process aiming to set a top list of diabetes related goals, as suggested by decision makers and health professionals. Methods A 2-step prioritization process, including a small (n = 32) circle of key opinion leaders of the INDC and a larger (n = 195) nationwide circle of diabetes health professionals consisting of physicians, nurses, and dieticians working in diabetes care centers, hospitals and family practice clinics, was established. An online questionnaire presenting 45 different action areas in diabetes prevention and care was distributed to the INDC members who ranked the 3 top diabetes priorities based on their individual interpretation of importance and applicability. The 7 highest ranking priorities were later presented to hospital-based and community diabetes health professionals. These professionals selected the 3 top priorities, based on their perceived importance. Results Council members opted mostly for action areas regarding specific populations, such as clinics for adult type-1 diabetes patients, diabetic foot, and pediatric and adolescent patients, while the health professionals’ top priorities were mostly in the general field of prevention, namely high-risk prediabetes population, prevention of obesity, and promotion of healthy life-style. In addition, priorities differed between hospital and community health professionals as well as between different professional groups. Conclusions A national prioritization process of action areas in diabetes prevention and care is attainable. The resulting item list is affected by professional considerations. These priorities may direct efforts in the implementation of interventions to improve national-level diabetes management. Supplementary Information The online version contains supplementary material available at 10.1186/s13584-022-00540-x.

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Emergence of opinion leaders in reference networks.

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Emergence of opinion leaders in reference networks.

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