A Study of Web-Based Scientific Research Collaboration System

Author(s):  
Yongqiang He
2017 ◽  
Vol 34 (8) ◽  
pp. 8-19
Author(s):  
Stacy Brody

Purpose The purpose of this paper is to profile various types of Web-based tools to facilitate research collaboration within and across institutions. Design/methodology/approach Various Web-based tools were tested by the author. Additionally, tutorial videos and guides were reviewed. Findings There are various free and low-cost tools available to assist in the collaborative research process, and librarians are well-positioned to facilitate their usage. Practical implications Librarians and researchers will learn about various types of tools available at free or at low cost to fulfill needs of the collaborative research process. Social implications As the tools highlighted are either free or of low cost, they are also valuable to start-ups and can be recommended for entrepreneurs. Originality/value As the realm of Web-based collaborative tools continues to evolve, the options must be continually revisited and reviewed for currency.


2018 ◽  
Vol 22 (7) ◽  
pp. 1471-1488 ◽  
Author(s):  
Antonio Usai ◽  
Marco Pironti ◽  
Monika Mital ◽  
Chiraz Aouina Mejri

Purpose The aim of this work is to increase awareness of the potential of the technique of text mining to discover knowledge and further promote research collaboration between knowledge management and the information technology communities. Since its emergence, text mining has involved multidisciplinary studies, focused primarily on database technology, Web-based collaborative writing, text analysis, machine learning and knowledge discovery. However, owing to the large amount of research in this field, it is becoming increasingly difficult to identify existing studies and therefore suggest new topics. Design/methodology/approach This article offers a systematic review of 85 academic outputs (articles and books) focused on knowledge discovery derived from the text mining technique. The systematic review is conducted by applying “text mining at the term level, in which knowledge discovery takes place on a more focused collection of words and phrases that are extracted from and label each document” (Feldman et al., 1998, p. 1). Findings The results revealed that the keywords extracted to be associated with the main labels, id est, knowledge discovery and text mining, can be categorized in two periods: from 1998 to 2009, the term knowledge and text were always used. From 2010 to 2017 in addition to these terms, sentiment analysis, review manipulation, microblogging data and knowledgeable users were the other terms frequently used. Besides this, it is possible to notice the technical, engineering nature of each term present in the first decade. Whereas, a diverse range of fields such as business, marketing and finance emerged from 2010 to 2017 owing to a greater interest in the online environment. Originality/value This is a first comprehensive systematic review on knowledge discovery and text mining through the use of a text mining technique at term level, which offers to reduce redundant research and to avoid the possibility of missing relevant publications.


2021 ◽  
Vol 16 (12) ◽  
pp. 68
Author(s):  
Xiangjin Xiao ◽  
Manoch Prompanyo

Collaboration in science is a complex phenomenon that affects scientific performance in various ways. Thus, understanding the influences of the research collaboration network is important for researchers. This paper explores the relationship between research collaboration network structural and scientific research performance and conducts an empirical test with data from 416 scholars. Findings revealed that network stability reduces the scholars' research performance, and network centrality promotes research performance. The network structural holes that the scholar spans, moderate the detrimental effects of network stability. This research provides suggestions for scholars to build a reasonable scientific research collaboration network to improve their research performance.


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