Tunali, V.Bilgin, T.T.2024-07-122024-07-1220149.78145E+1210.1145/2659532.26596392-s2.0-84908695747https://doi.org/10.1145/2659532.2659639https://hdl.handle.net/20.500.12415/7412Querbie;University of Ruse (UORB)15th International Conference on Computer Systems and Technologies, CompSysTech 2014 -- 27 June 2014 through 28 June 2014 -- -- 108747In this study, we examined 6,834 master's and PhD theses conducted on computer science and engineering between 1994 and 2013 in Turkey. Thesis data were compiled from the YÖK national thesis database web portal. We used text mining techniques to extract research concepts and their co-occurrence data from graduate thesis abstracts. Then, we applied social network analysis techniques on the concept cooccurrence networks to visually explore core research concepts, and connections and relationships among them. We showed that text mining and social network analysis techniques together were very effective for knowledge discovery in scientific documents in computer science and engineering domain. Copyright © 2014 ACM.eninfo:eu-repo/semantics/closedAccessComputer EngineeringComputer ScienceGraduate ThesesSocial Network AnalysisText MiningConference Object193N/A187883