The aim of this study is to analyze and describe the research front within information science. To reach this purpose we ask the following research question: Which research themes can be identified within the subject field of information science by using bibliographic coupling in combination with cluster analysis.The data for our study consists of articles from the journals Journal of the American Society for Information Science and Technology and Journal of Documentation throughout the years 2004-2006. The bibliographic information from the articles was analyzed with the combined methods of bibliographic coupling and cluster analysis. This gave fifteen clusters within which we identified research themes. When analyzing these results we found four main fields of research within the research front of information science: Information retrieval, bibliometrics, knowledge organization and information science as research discipline. Information retrieval proved to be the largest field of research followed by bibliometrics and thereafter the two significantly smaller fields of research knowledge organization and information science as research discipline. When comparing our results with previous research we found that despite different choice of methods and data, there were some similarities. / Uppsatsnivå: D

This paper aims to map and contrast the research front and theresearch base of Library and Information Science (LIS) inScandinavia during 1980-1989 and 2003-2013 from articlespublished in Web of Science.The research questions are:1. How is the research base and research front in LIS inScandinavia between 1980-1989 and 2003-2012 structured?2. What differences can be observed between the two time periods1980-1989 and 2003-2012 with regards to the research base?3. What differences can be observed between the two time periods1980-1989 and 2003-2012 with regards to the research front?This study is based on bibliometrical methods and uses authorco-citation analysis and bibliographic coupling. To interpret theresults a cluster analysis were made by using the applicationVosviewer. When the cluster analysis were made, a contentanalysis were done on the titles of publications from the clusteranalysis to determine what subject category they belonged to.The results indicates that the field of LIS has a large focus oninformation science, there were hardly any trace of the libraryaspect of the field. The study also showed that the bibliometricfield has grown since 1980-1989. It was also clear that hard andsoft information retrieval had grown apart. / Program: Bibliotekarie

Objectives: The aim in this thesis has been to generate information relevant for strategic positioning and future evaluations within the scientific field of sport and exercise psychology. This has been done by request, and in collaboration with The Group of Sport and Exercise Psychology at the Institution of Psychology at the University of Umeå. Research questions:  (1) How does the cognitive structure within the field of sport and exercise psychology take shape with respect to research topics in current sport-psychological research, i.e. the research front? (2) How does the social structure within the field of sport and exercise psychology take shape with respect to formal scientific collaboration? Data: 879 articles published between 2008-2011 were used in this study. The population of articles were collected from a set of 5 core journals: International Journal of Sport Psychology, Journal of Applied Sport Psychology, Journal of Sport and Exercise Psychology, The Sport Psychologist, Psychology of Sport and Exercise. The original set was expanded by collecting relevant sport psychology articles from Scandinavian Journal of Medicine & Science in Sports and Journal of Sports Sciences. Methods: (1) The bibliometric indicator normalized bibliographic coupling combined with hierarchical agglomerative cluster analysis was used for mapping the research front. With this approach articles are basically clustered with respect to shared refererences, which in this context is understood as a measure of topical similarity. (2)  For the mapping of social structures a collaboration analysis was performed by extracting and visualizing social networks based on the bibliometric indicator coauthorship.     Results: (1) Identification and classification of 80 clusters based on topical similarity in collaboration with a subject expert. (2) Providing a map of formal scientific collaborations between countries based on coauthorship. (3) Providing a map of social networks based on coauthorships between individual researchers. (4) Identification and contextualization of central researchers based on production within the visualized coauthor network. The publications of each researcher were traced to corresponding clusters in the research front to gain information about in which subject areas and topics these central researchers publish. (5) Identification of research groups with high coauthor values, i.e. high intensity in their formal collaboration. Furthermore the publications from these groups were connected to corresponding clusters, i.e. giving information about in which subject areas and topics these groups publish.