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social network that to write scientific articles

social network that to write scientific articles

 


3. Materials and Methods The sample that we used for our research was acquired from Scopus, the largest multidisciplinary bibliographical abstract and citation search database [89]. Despite the apparent importance of the topic, there has been little analytical research on co-authorship and co-citation networks in the field of agricultural economics. According to the InCites Journal Citation Reports, there were 17 journals in category of agricultural economics and policy in 2016. In this rank the top six journals are the following: 1. Food Policy, IF = 3.086. 2. American Journal of Agricultural Economics, IF = 1.829. 3. Australian Journal of Agricultural and Resource Economics, IF = 1.826. 4. Journal of Agricultural Economics, IF = 1.795. 5. Agricultural Economics, IF = 1.758. 6. European Review of Agricultural Economics, IF = 1.6. Food Policy with the highest impact factor was selected for our research because it is a multidisciplinary journal on issues in implementation and evaluation of policies for the food sector Sustainability 2018, 10, 577 7 of 20 in developing, transition, and advanced economies considering papers from any of the social sciences. Furthermore, Food Policy prioritize economic and social aspects of empirical studies on international food policy debates and is the most relevant journal with its highest ranking in the field of agricultural economics. The basis of our sample is comprised of the 714 papers published between 2006 and 2015. Altogether, these papers originated from 1708 different authors. If redundancies are also taken into consideration, this number is 2119. In our analysis, we also examined the 8749 citations referring to these papers, 6456 of which originated from different papers. Altogether, the examined sample consists of 6838 papers, not considering redundancies. The database of our sample contains the following tables: affiliation (affiliation_id, name, city, country); articles (article_id, journal_id, volume, issue, first, last, title, source_type); articles_authors (article_id, author_id); authors (author_id, name, surname, givenname, initilas, affiliation_id); cited (article_id, cited_article_id); journals (journal_id, name); keywords (article_id, keyword); subjects (article_id, subject). Network Analysis Gephi is an open source network exploration and manipulation software. Developed modules can import, visualize, spatialize, filter, manipulate, and export all types of networks. The visualization module uses a special 3D render engine to render graphs in real-time. This technique uses the computer graphics card, as video games do, and leaves the CPU free for other computing. It can deal with large networks (i.e., over 20,000 nodes) and, because it is built on a multi-task model, it takes advantage of multi-core processors. The user interface is structured into Workspaces, where separate work can be done, and a powerful plugin system is currently being developed. Great attention has been taken to the extendibility of the software. An algorithm, filter, or tool can be easily added to the program, with little programming experience. Sets of nodes or edges can be obtained manually or by using the filter system. Filters can select nodes or edges with thresholds, ranges, and other properties. In practice, filter boxes are chained, each box takes in input, the output of the upper box [90]. Dynamic network visualization