The main purpose of this bachelor thesis is to analyse the publication- and citation patterns of the articles concerning bibliometrics, informetrics, scientometrics, and webometrics which can be found on Web of Science, and give a brief description of how the definition of the four terms has developed. I have looked at how the number of published papers have developed over the years and to what extent they have been quoted by other researchers. I have also briefly adressed what other research fields are referring to articles published in the four areas. The material I looked at includes articles that can be found on Web of Science with one (or more) of the four terms as topic and are categorised under library- and information science starting with the first bibliometrics article which was published in 1969, and ending in 2013. The results show that the publications in all four fields are continuously increasing. For bibliometrics and scientometrics it shows a slow increase up until 2005, then increasing exponentially. Informetric seems to be a comparatively small topic and webometrics is increasing, but is still a relatively young topic which makes it hard to make any concrete conclusions Regarding the citations, it shows that citations for the bibliometrical articles have had a steady curve increasing up until 2005, and then decreasing, the informetric- and scientometrical articles have rather scattered results and the webometrics have decreasing results, which I deduce is based on the fact that it is a new field and citations do not appear until after a few years. Finally I recommend future research, based on the related research I have found.

The purpose of this thesis is to evaluate the combination of bibliographic coupling and three hierarchical cluster analytic techniques: average, complete and single linkage. Bibliographic coupling is applied as a measure of similarity between recently published articles and the cluster techniques are used for the partition of a set of articles into subsets of articles with similar research focus. The field of information science is applied as the test arena and the selection of data, i.e., the article population to be partitioned, is based on a number of central journals. Methods of evaluation include both quantitative approaches as well as a qualitative one. For comparing the resulting partitions, adjusted Rand index is utilized and for the establishment of cluster coherence and isolation, measures of average normalized coupling strength is applied. In an effort to quantify the degree of subject focus within clusters, normalized entropy of a cluster’s distribution of weighted descriptors is calculated. Manual inspection of cluster composition is also performed. The findings show that choice of cluster method has a profound impact on the resulting partitions. Complete linkage generated highly subject coherent clusters but produced a fragmented picture of the research field in question, i.e., the split up of research specialties. Single linkage on the other hand, performed unsatisfactory and is not recommended. It is suggested that average linkage, when combined with a stopping rule (the inconsistency coefficient), should be considered as the method of choice since it mainly generated reasonable subject coherent clusters while avoiding severe fragmentation. / Uppsatsnivå: D

The purpose of this Bachelor’s thesis is to explore the useability of bibliometric analysis on scientists of the humanities. This is accomplished by doing a case study on philosopher Slavoj Žižek. The work process and the results the case study is able to produce and the limits of these results are then analysed and discussed.In the case study all scientific articles in English published 1987-2010 citing Žižek were analysed. The material was gathered from the databases provided by Thomson Reuters through the Web of Science.Most references to Žižek were published in Cultural Critique, a transdisciplinary journal published in the USA. Organizational behaviourist De Cock had the most references, but literature studies was the most common institution among the authors. The 15 most cited works are monographs, and the most cited is The sublime object of ideology. The most cocited works are by psychoanalyst Lacan or works about his theories.The results show that an analysis of a researcher of the humanities using bibliometric methods provide us with relevant information. However, this information is not as complete as when applied on a scientist in the natural sciences. The main reason for this is the differences in publication behaviour and the lack of relevant material in the databases covering the humanities.Several suggestions for further research is given. These concern more in depth studies of the citations of Žižek, comparative studies using other databases, and the changes in publication patterns within the humanities. / 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.

To look for scientific literature, there are specialized databases and search engines to simplify the process. In order to quickly assess the quality of a given paper, there are different indices meant to quantify the success and impact an author has had within the scientific community. However, these indices have some flaws and could potentially be exploited. In this thesis, we aim to gather publication data from cyber security conferences, identify unknown patterns and trends as well as to introduce a new index or metric that better captures the impact of authors in the field than current common indices. We found that the cyber security community is in a healthy state with no obvious exploitation of common indices. With one notable exception, there is near equal distribution between citations within sub-communities and outside of them. We also found that the majority of authors with several publications chose to publish for several different conferences, not just one of them. Furthermore, new and growing trends in cyber security research were found to be ”machine learning”, ”blockchain” and ”differential privacy”. As for the conferences, it appears that USENIX has overtaken CCS in recent years as the conference with the highest publication output. While no attempts to exploit the common indices were identified, we believe that the risk is still there. We also identify other flaws with the usage of the common metrics in the cyber security research field. As such, we suggest the adoption of the pure R-index with a normalized proportional counting as the score calculation method, since it takes the number and order of the authors into consideration, as well as that it does not discriminate against authors with few publications with many citations. / För att hitta vetenskaplig literatur finns det särskilda databaser och sökmotorer för att förenkla processen. För att snabbt kunna uppskatta kvaliteten hos en given vetenskaplig text finns det olika index menade att snabbt och enkelt kunna kvantifiera en författares inflytande och framgång inom vetenskapen. Det finns dock brister och sätt att utnyttja dessa index. I den här rapporten har vi som mål att samla in data från datasäkerhetskonferenser, identifiera okända mönster och trender samt att introducera ett nytt index som bättre fångar författares inflytande än nuvarande standarder. Vi fann att cyberäkerhet som forskningsområde är välmående och utan uppenbara utnyttjanden av de vanligaste indexen. Med ett enda undantag sker det nästan lika mycket citeringar mellan olika delgemenskaper som inom dem. Vi fann även att majoriteten av författare med flera publikationer valt att publicera i flera olika konferenser och inte bara en. Vidare fann vi att ”machine learning”, ”blockchain” och ”differential privacy” är nya och växande trender. Vad gäller konferenser visar det sig att USENIX har gått om CCS på senare år som den konferens med störst publikationsutflöde. Även om vi inte identifierade något missbruk tror vi att det fortfarande finns risk för det. Vi identifierade även andra brister med användningen av de vanligaste indexen i cybersäkerhetsforskningsområdet. Av dessa anledningar föreslår vi användningen av det så kallade ”pure R-index” med en normaliserad proportionell räkning som poängberäkningsmetod, eftersom att det tar antalet samt ordningen av författare i hänsyn, samt att det inte heller diskriminerar mot författare med få publikationer med många citeringar.