Data Mining In Authorship Collaboration Paper
2.2 Data Mining in Authorship Collaboration
Nowadays, data mining in authorship collaboration gaining interest and demand among the researchers. Data mining techniques have been applied successfully in many areas from traditional areas such as business and science (Fu, 1997). A lot of organizations now employ data mining as a secret weapon to keep or gain competitive edge. The application of data mining techniques is becoming increasingly important in modern organizations that seek to utilize the knowledge that is embedded in the mass organizational data to improve efficiency, effectiveness and competitiveness (Akkaya & Uzar, 2011). Data mining is able to uncover hidden patterns and relationship among the academicians in the higher education
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Previous research works have focused on defining elements such as network structure and typology that are meaningful to be analysed within these networks. Authorship collaboration (co-authorship) network includes research analytics (Rachela & Hu, 2010; Nikzad et al., 2011). Research analytic is a research field that utilizes mathematical and algorithmic methods for analysing the way research takes place and it can provide meaningful data for researchers (Harmelen & Workman, 2012). Research analytics are also used for analysing research collaboration towards identifying meaningful patterns and …show more content…
In addition, SNA is the quantitative analysis method applied and related to the study of social relationship especially in authorship collaboration studies. Meanwhile, Cheong & Corbitt (2009) describes SNA is helping to gain an understanding of the nodes (co-authors) and relationships (those who wrote a paper together) in the co-authorship network that consists of structural dimension (centrality) and relational dimension (tie strength). Structural dimension includes the number of relations within a network; the relative access to information each network actor has and the centrality of each network actor (Wise, 2012) while relational dimension governs relationships between individual actors in a network which is measure of tie strength. The findings of the study will be used in determine the links and relationship of the academicians toward improving the quality of
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