Authors:Yiwei Xia, Yanying Fan, Tzu-Hsuan Liu, and Zhihao Ma
measures of peer effects, which revealed inconsistent findings. A recent narrative review ( Hoeben, Meldrum, Walker, & Young, 2016 ) suggested that future studies should use a socialnetworkanalysis (SNA) to measure objective peer effects, while avoiding
is still needed to understand the gap between collaborative tagging system users and IO professionals.
This article uses socialnetworkanalysis (hereafter SNA) and the frequent-pattern tree (hereafter FT tree) method to identify the patterns
Authors:Zaida Chinchilla-Rodríguez, Anuska Ferligoj, Sandra Miguel, Luka Kronegger, and Félix de Moya-Anegón
analysis and socialnetworkanalysis to establish new perspectives for analysing scientific collaboration networks and monitoring individual and group careers.
Data and methods
The methodology combines three approaches. Two
Authors:Gohar Feroz Khan, Junghoon Moon, and Han Woo Park
researchers (e.g., citation analysis and co-authorship analysis) (Hou et al. 2008 ; Lu and Feng 2009 ; Newman 2001a ; Park et al. 2005 ; Park and Leydesdorff 2008 ; Pritchard 1969 ).
However, in this article, we used socialnetworkanalysis
directly reveal the fronts or academic commanding points in the development and evolution of knowledge, which are widespreadly paid attention to (Liu et al. 2008 ).
The focus of socialnetworkanalysis (SNA) is on the relationships among social
Previous studies on scientific communities or on knowledge diffusion in large have either focused on co-authorship relations or semantic relations. As mentioned in Sect. 2 , there are a few number of studies which have
Authors:Peter Mika, Tom Elfring, and Peter Groenewegen
The use of electronic data is steadily gaining ground in the study of the social organization of scientific and research communities,
decreasing the researcher's reliance on commercial databases of bibliographic entries, patents grants and other manually constructed
records of scientific works. In our work we provide a methodological innovation based on semantic technology for dealing with
heterogeneity in electronic data sources. We demonstrate the use of our electronic system for data collection and aggregation
through a study of the Semantic Web research community. Using methods of network analysis, we confirm the effect of Structural
Holes and provide novel explanations of scientific performance based on cognitive diversity in social networks.
Authors:Janghyeok Yoon, Sungchul Choi, and Kwangsoo Kim
socialnetworkanalysis (SNA) to identify trends from word co-occurrences (Lee and Jeong 2008 ; Callon et al. 1991 ). However, to identify occurrences of keywords, CWA should define in advance a set of keyword or key phrase patterns which are
Authors:Jyun-Cheng Wang, Cheng-hsin Chiang, and Shu-Wei Lin
Patents are important intellectual assets for companies to defend or to claim their technological rights. To control R&D cost,
companies should carefully examine their patents by patent quality. Approaches to evaluating patent quality are mostly a posteriori
uses of factual information of patent quality. This paper examined whether patent quality can be predicted a priori, i.e.,
during the early years after a patent is granted, by analyzing information embedded in a network of patent citations. Social
network analysis was applied to analyze two network positions occupied by a patent, brokerage and closure to determine whether
either position is a good predictor of patent quality. Patent renewal decisions and forward citations were adopted as surrogates
of patent quality. The analytical results showed that forward citations can be positively predicted by the brokerage position
and negatively predicted by the closure position in the early and mature stages. Renewal decisions can be negatively predicted
by the brokerage position in the early stage, and the closure position influences the renewal decision in a different way
in the early and mature stages. These analytical results imply that a company should focus on developing patents that bridge
different technologies as its technological developments reach maturity.
Based on a face-to-face survey of 312 scientists from government research institutes and state universities in two Philippine
locations — Los Baños, Laguna and Muñoz, Nueva Ecija — we examine how graduate training and digital factors shape the professional
network of scientists at the “Global South.” Results suggest that scientists prefer face-to-face interaction; there is no
compelling evidence that digitally-mediated interaction will replace meaningful face-to-face interaction. What is evident
is that among none face-to-face modes of communication a reordering maybe in progress.
The effect of digital factors — expressed through advance hardware-software-user interaction skills — lies on network features pertaining to size, proportion of male and of core-based alters, and locational diversity. International
graduate training and ascribed factors (gender and number of children) also configure the professional network of scientists — actors traditionally viewed as the epitome of rationality and objectivity. We argue that these factors influence knowledge production through a system of patronage and a culture that celebrates patrifocality. We forward the hypothesis that knowledge production at the “Global South” closely fits Callon’s  extended translation model of science.