Doctoral dissertations of Library and Information Science in China: A co-word analysis

Zong, Qianjin; Shen, Hong-Zhou; Qinjian, Yuan; Hu, Xiaowei; Hou, Zhiping; Deng, Shun-Guo

doi:10.1007/s11192-012-0799-1

Cited by 105 publications

(77 citation statements)

References 47 publications

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“…Las palabras clave con alta centralidad de intermediación fueron arquitectura de la información, gestión de la información, comportamiento de la información y gestión del conocimiento. También identificaron 63 palabras clave en el centro-periferia que representan el foco de investigación en la bibliotecología y ciencia de la información china, entre las cuales Zong et al (2013) analizaron las palabras clave de las tesis de doctorado en bibliotecología y ciencia de la información en China en el periodo de 1994 a 2011. Recolectaron los datos por medio de seis bases de datos de tesis que son de acceso público y que forman parte de los recursos de información de las universidades chinas que están autorizadas por el gobierno para otorgar grados de doctor en esta área del conocimiento.…”

Section: Revisión De La Literaturaunclassified

Red de co-palabras en la bibliometría mexicana

Restrepo-Arango

Alvarado

2017

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ResumenSe realizó un análisis de co-palabras utilizando las palabras clave en los documentos publicados sobre las metrías (bibliometría, informetría, cienciometría, patentometría, etc.) en México desde la década de 1970 hasta diciembre de 2012. Se usó el análisis de co-ocurrencia de palabras, la agrupación jerárquica y el mapa de la red social. Estas técnicas se aplicaron a 681 palabras clave (PC) con 1 914 ocurrencias contenidas en 459 artículos. Se encontró que las palabras clave con la mayor ocurrencia son "Bibliometría" (10.6 %), "México" (6.3 %), "Producción científica" (3 %), "América Latina" (3 %), "Factor de impacto" (1.8 %), "Indicadores bibliométricos" (1.8 %) y "Cienciometría" (1.7 %). La

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Section: Revisión De La Literaturaunclassified

Red de co-palabras en la bibliometría mexicana

Restrepo-Arango

Alvarado

2017

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“…theses (examples are: Anunobi, 2002Riahinia, 2010;Sexton, 2006;Waugh & Ruppel, 2004). Ph.D. dissertations have also received attention from citation analysis researchers who regard dissertations as being a good indication of which material is being used (examples are: Conkling, Harwell, McCallips, Nyana, & Osif, 2010;Gooden, 2001, Iivonen et al, 2009, Kaczor, 2014Kumar & Dora, 2011;Nabe & Imre, 2008;Kushkowski et al, 2003;Maz-Machado et al, 2012;Romić & Mitrović, 2014;Zafrunnisha & Pulla Reddy, 2010;Zong et al, 2013). Whereas several studies do investigate citation patterns of faculty members (for example : Currie & Monroe-Gulick, 2013;Lightman & Manilov, 2000;Pancheshnikov, 2007), the information gleaned from doctoral research can also serve as an indicator for faculty research patterns (Zipp, 1996).…”

Section: Application Of Citation Analysis -Usersmentioning

confidence: 99%

Citation Analysis of M.A. Theses and Ph.D. Dissertations in Sociology and Anthropology: An Assessment of Library Resource Usage

Rosenberg

2015

The Journal of Academic Librarianship

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“…Co-word analysis is based on counting and analyzing the co-occurrences of words in different parts of articles of a specific domain (Callon et al 1991). Most of the previous research used co-word analysis to depict structures of different scientific domains such as biotechnology (Rip and Courtial 1984), acidification research (Law and Whittaker 1992), biological safety (Cambrosio et al 1993), patents , scientometrics (Courtial 1994), drug industry (Rikken et al 1995), software engineering (Coulter et al 1998), information retrieval research (Ding et al 2001), document retrieval (Hui and Fong 2004), R&D domain of robot technology (Lee and Jeong 2008), stem cells field (An and Wu 2011), visualization methods (Yang et al 2012), doctoral dissertation (Zong et al 2013), intellectual structure (Cho 2014).…”

Section: Co-word Analysis Of Text-miningmentioning

confidence: 99%

Analysis of research papers on E-commerce (2000–2013): based on a text mining approach

Bei-ni

Lee

2015

Scientometrics

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E-commerce (EC) is sweep across the globe and has become a most important commercial activity. Accordingly, EC also causes the academia's research interests. A lot of research achievements have been gained in recent years. This paper takes these achievements as research object and collects 8488 research papers published in academic journals during 2000-2013 included in Web of Science database. Using text mining techniques, 68 terms are identified as the main keywords of EC field. Then the scientific structure of the EC is mapped through multidimensional scaling, based upon the cooccurrence of the main terms in the academic journals. The results show that the EC domain is composed of three main fields, such as technology, management and customer. Furthermore, knowledge graph based on the EC research network is visualized and it shows that the whole EC research papers covering seven important subnets, which are: internet, consumer behaviour, customer satisfaction, online shopping, reputation, Taiwan and knowledge management.

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Doctoral dissertations of Library and Information Science in China: A co-word analysis

Cited by 105 publications

References 47 publications

Red de co-palabras en la bibliometría mexicana

Red de co-palabras en la bibliometría mexicana

Citation Analysis of M.A. Theses and Ph.D. Dissertations in Sociology and Anthropology: An Assessment of Library Resource Usage

Analysis of research papers on E-commerce (2000–2013): based on a text mining approach

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