{"title":"Social Network Analysis in Wood Industry Projects","authors":"A. Novotni, Z. Pásztory, Z. Tóth","doi":"10.37045/aslh-2022-0006","DOIUrl":null,"url":null,"abstract":"The study analysed H2020 projects in the wood industry using SNA methods. It was mainly performed using R. Based on the data set from CORDIS, an adjacency matrix was constructed and used to plot the network of project participants. Various network indicators were then calculated. In search of notable distributions in network research, several statistical methods (maximum likelihood, Kolmogorov-Smirnov test, moments, bootstrapping) were used to perform a goodness-offit analysis on the frequencies of the degrees to verify randomness or scale-freedom. The small-world nature was also investigated. The results show that the distribution of the degrees of project participants reflects multiple effects, whereas the number of project participations per project participant follows a power distribution; thus, the scale-freedom that has been emphasised in many scientific analyses is observed. The network indicators show that the network is not small-world, with a high number of Finnish participants among the central actors.","PeriodicalId":53620,"journal":{"name":"Acta Silvatica et Lignaria Hungarica","volume":"65 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Silvatica et Lignaria Hungarica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37045/aslh-2022-0006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
The study analysed H2020 projects in the wood industry using SNA methods. It was mainly performed using R. Based on the data set from CORDIS, an adjacency matrix was constructed and used to plot the network of project participants. Various network indicators were then calculated. In search of notable distributions in network research, several statistical methods (maximum likelihood, Kolmogorov-Smirnov test, moments, bootstrapping) were used to perform a goodness-offit analysis on the frequencies of the degrees to verify randomness or scale-freedom. The small-world nature was also investigated. The results show that the distribution of the degrees of project participants reflects multiple effects, whereas the number of project participations per project participant follows a power distribution; thus, the scale-freedom that has been emphasised in many scientific analyses is observed. The network indicators show that the network is not small-world, with a high number of Finnish participants among the central actors.