Article type
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Abstract
Background:
Knowledge translation is a key element of evidence-informed healthcare decision making. Social media like Facebook and Twitter provide a rapid and easily accessible platform for wider dissemination of systematic reviews and are an integral mode of communication for a global organization like Cochrane with diverse stakeholders.Objectives:
To evaluate the formation of network structures and to analyze the clusters and key influential person within clusters.Methods:
We downloaded data from the Cochrane Facebook Group (https://www.facebook.com/groups/63721740498/) by using Netvizz application (https://apps.facebook.com/netvizz/) on 23 March 2015. We imported the data file to visualize it via a software called Gephi. We applied the Mathieu Jacomy’s Force Atlas 2 algorithm layout to evaluate network patterns and to identify social network clusters.Results:
Overall there were 8577 users in the Cochrane Group. However we could download data for only 4762 users(nodes) since there is a restriction in the app for the amount of data that can be downloaded. The gender distribution was 51.3 % males and 47.5% females and the remaining 1.13% were unspecified . Members of these groups speak 55 different languages.One user in this network has been identified as a highly influential user with more than 75 connections within the group; 2504 (52.2%) users who are members of the group, do not have any network relations with each other (Fig1). We have identified nine clusters based on a modularity algorithm using the connections (edges) and in each cluster there are one or two influential users who have a relationship with almost everyone within that cluster (Fig2). We also identified 7 users who act as conduits between different clusters but most of them are not the key-influencers (Fig3).