Data ownership is of fundamental importance in the digital economy of today. Commercializing academic research, whilst maintaining ownership of it, is a task that can now be accomplished due to the strengths of blockchain technology, which allows data to be registered, made unique, and traced to its origins. We propose a blockchain use-case for licencing academic research, based off an academic project named UniCoin. In this thesis, we discuss how to fairly attribute credit between all sources of knowledge that contribute to new pieces of academic research, using citation network analysis and centrality measures. Katz centrality, in-degree centrality, and PageRank are three potentially useful centrality measures, with varying results: these are compared using case studies based on three papers co-authored by Andrei Shleifer. We use these centrality measures to guide how to fairly attribute credit, and thus how to distribute licencing revenues generated through UniCoin.

Thesis (MSc)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: Citation analysis is an important tool in the academic community. It can aid universities, funding bodies, and individual researchers to evaluate scientific work and direct resources appropriately. With the rapid growth of the scientific enterprise and the increase of online libraries that include citation analysis tools, the need for a systematic evaluation of these tools becomes more important. The research presented in this study deals with scientific research output, i.e., articles and citations, and how they can be used in bibliometrics to measure academic success. More specifically, this research analyses algorithms that rank academic entities such as articles, authors and journals to address the question of how well these algorithms can identify important and high-impact entities. A consistent mathematical formulation is developed on the basis of a categorisation of bibliometric measures such as the h-index, the Impact Factor for journals, and ranking algorithms based on Google’s PageRank. Furthermore, the theoretical properties of each algorithm are laid out. The ranking algorithms and bibliometric methods are computed on the Microsoft Academic Search citation database which contains 40 million papers and over 260 million citations that span across multiple academic disciplines. We evaluate the ranking algorithms by using a large test data set of papers and authors that won renowned prizes at numerous Computer Science conferences. The results show that using citation counts is, in general, the best ranking metric. However, for certain tasks, such as ranking important papers or identifying high-impact authors, algorithms based on PageRank perform better. As a secondary outcome of this research, publication trends across academic disciplines are analysed to show changes in publication behaviour over time and differences in publication patterns between disciplines. / AFRIKAANSE OPSOMMING: Sitasiesanalise is ’n belangrike instrument in die akademiese omgewing. Dit kan universiteite, befondsingsliggams en individuele navorsers help om wetenskaplike werk te evalueer en hulpbronne toepaslik toe te ken. Met die vinnige groei van wetenskaplike uitsette en die toename in aanlynbiblioteke wat sitasieanalise insluit, word die behoefte aan ’n sistematiese evaluering van hierdie gereedskap al hoe belangriker. Die navorsing in hierdie studie handel oor die uitsette van wetenskaplike navorsing, dit wil sê, artikels en sitasies, en hoe hulle gebruik kan word in bibliometriese studies om akademiese sukses te meet. Om meer spesifiek te wees, hierdie navorsing analiseer algoritmes wat akademiese entiteite soos artikels, outeers en journale gradeer. Dit wys hoe doeltreffend hierdie algoritmes belangrike en hoë-impak entiteite kan identifiseer. ’n Breedvoerige wiskundige formulering word ontwikkel uit ’n versameling van bibliometriese metodes soos byvoorbeeld die h-indeks, die Impak Faktor vir journaale en die rang-algoritmes gebaseer op Google se PageRank. Verder word die teoretiese eienskappe van elke algoritme uitgelê. Die rang-algoritmes en bibliometriese metodes gebruik die sitasiedatabasis van Microsoft Academic Search vir berekeninge. Dit bevat 40 miljoen artikels en meer as 260 miljoen sitasies, wat oor verskeie akademiese dissiplines strek. Ons gebruik ’n groot stel toetsdata van dokumente en outeers wat bekende pryse op talle rekenaarwetenskaplike konferensies gewen het om die rang-algoritmes te evalueer. Die resultate toon dat die gebruik van sitasietellings, in die algemeen, die beste rangmetode is. Vir sekere take, soos die gradeering van belangrike artikels, of die identifisering van hoë-impak outeers, presteer algoritmes wat op PageRank gebaseer is egter beter. ’n Sekondêre resultaat van hierdie navorsing is die ontleding van publikasie tendense in verskeie akademiese dissiplines om sodoende veranderinge in publikasie gedrag oor tyd aan te toon en ook die verskille in publikasie patrone uit verskillende dissiplines uit te wys.

世界各國政府在知識經濟的潮流之下更加重視本土學術研究的品質，各國投注資源以提升學術研究水準、促進學術社群的國際化。台灣順應此種趨勢，近年制定各種學術政策與評鑑計畫，其中推動學術社群的知識生產品質，是國家政策中既定的一項重點目標。台灣社會學門的知識生產也受到國家施政方向的影響，國家科學委員會於 1997、2001與2006年執行三波的社會學門專業期刊排序計畫，針對社會學門的學術期刊進行評比。 本研究著眼於此種學術場域的改變，將主要的研究關懷聚焦在學術社群的知識變遷；回顧科學社會學的研究傳統，引用行為是探查學社群知識生產的重要指標，引用代表學術知識傳遞與溝通的情形；而近年社會網絡分析（Social Network Analysis） 研究的興起，更擴充知識引用的研究方式與概念，採以引用網絡（Citation Networks） 分析知識結構與社群互動行為。本研究立基於社會網絡的研究概念，利用網絡分析工具試圖捕捉當代台灣社會學知識引用結構的現狀；社會學門的知識引用結構；究竟學術知識的引用會有何種變遷？引用的機制為何？ 本研究採用2007年第三波社會學門專業期刊排序資料，進行次級資料分析，研究問題環繞在2001~2006年引用網絡結構的多層次架構，開展出三項研究問題： （一）社會學門學術期刊引用網絡的現況，互引網絡結構的動態變化為何？ （二）社會學門內部學者引用期刊的情形為何？社會學門各類型期刊的引用變遷又如何？ （三）以社會學門期刊引用的產生是偏向於以內容為主的規範論或符合以社會關係為主的建構論的機制？ 研究結果分成三部份。第一，在期刊對期刊引用網絡層次部份，顯示學術期刊的引用網絡結構朝向集中化的趨勢，《台灣社會學》、《台灣社會學刊》成為引用結構中主要被引用的學術期刊組織，而且成為引用網絡結構中優勢地位的引用副團體。第二，社會學門學者引用學術期刊的雙元網絡層次，顯示社會學者與社會福利、社會工作學者的引用分流；社會學專業期刊與社會工作專業期刊的引用也存在著分流的情形。最後，《台灣社會學》、《台灣社會學刊》與《台灣社會研究季刊》的社會學者引用機制為內容為主的規範論。此三項結果顯示期刊排序制度施行社會學門的學術期刊，特定學術期刊的學術論文被其他期刊所肯定，產生引用結構的集中化變遷，同時社會學者與社會福利、社會工作學者對學科專業期刊分流引用也逐漸成形。而三種學術期刊內，社會學者的引用網絡影響來自於學者專長的相同與否，更是為台灣社會學的知識引用現狀，提出一個解釋的答案。 / Abstract In recent years, as the world has been trending toward a Knowledge-based Economy, governments worldwide have recognized the importance of academic research, providing resources to upgrade the academic research level in order to internationalize scholarly pursuit. Taiwan, as a latecomer to the concept of Knowledge-based Economy, has begun to constitute science and social science rules and evaluations for academic development. The study intends to capture the transformation of the academic field by examining citations. In early works in the science of sociology, citation was an important indication of scholarly productivity. Social network analysis (SNA) enriches the methodology, and makes the indication to the idea of citation networks. Based on the perspective of SNA, the study investigates the citation network database of sociological journals between 2001 and 2006, and the concurrent citation networks of sociologists from three prior sociological journals. The results include three parts: first, the structure of journals' citation networks shows the trend of centralization, and two academic journals attain privileged status by means of structural equivalence. Second, the dual network of authors and journals demonstrate the citation divisions of sociologists and social workers. The sociological professional journals and social worker professional journals also are divided by time. Finally, the citation mechanism of sociologists verifies the normative pattern. In conclusion, the analysis confirms the impact of social science policy, which influences the centralization of citation networks and the advantageous status of specific sociological journals. The sociologists' citation networks are related to the specialty similarities of scholars, not the social relations. The study gives a pioneer explanation of citation networks of Taiwanese sociology.