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Book part
Publication date: 3 June 2008

H. Frank Cervone

University libraries have traditionally been the primary caretaker of scholarly resources. However, as electronic modes of information delivery replace print materials…

Abstract

University libraries have traditionally been the primary caretaker of scholarly resources. However, as electronic modes of information delivery replace print materials, expectations of academic libraries have evolved rapidly. In this environment, academic libraries need to be adaptable organizations. Librarianship, though, is deeply rooted in strong values and beliefs which inherently limit receptivity to change and innovation, but these constraints are not absolute. Social network research indicates that professional advice networks play a significant role in how one thinks about and performs work and that individual perspectives are broadened when diverse input is received. Based on social network analysis methods, this study explored the relationship between individual receptivity to innovation and the composition of a person's professional advice network through a purposive sample of academic librarians in Illinois. The group completed a survey that explored two dimensions: (1) the nature of relationships within their professional advice network and (2) the individual's personal receptivity to innovation. Analysis of the nature of relationships within the professional advice networks was based on a combination of quantitative and qualitative techniques, in contrast to the analysis of the respondents’ receptivity to innovation which was based on quantitative measures. Based on the information from the 440 respondents, the results of this research indicate that there is a relationship between the size of the professional advice networks and individual's receptivity to innovation, but additional aspects of the professional advice network may play a role in an individual's overall receptivity to innovation.

Details

Advances in Library Administration and Organization
Type: Book
ISBN: 978-0-7623-1488-1

Article
Publication date: 19 January 2021

Hong Zhao, Yi Huang and Zongshui Wang

This paper aims to systematically find the main research differences and similarities between social media and social networks in marketing research using the bibliometric…

1006

Abstract

Purpose

This paper aims to systematically find the main research differences and similarities between social media and social networks in marketing research using the bibliometric perspective and provides suggestions for firms to improve their marketing strategies effectively.

Design/methodology/approach

The methods of co-word analysis and network analysis have been used to analyze the two research fields of social media and social networks. Specifically, this study selects 2,424 articles from 27 marketing academic journals present in the database Web of Science, ranging from January 1, 1996 to August 8, 2020.

Findings

The results show that social networks and social media are both research hotspots within the discipline of marketing research. The different intimacy nodes of social networks are more complex than social media. Additionally, the research scope of social networks is broader than social media in marketing research as shown by the keyword co-occurrence analysis. The overlap between social media and social networks in marketing research is reflected in the strong focus on their mixed mutual effects.

Originality/value

This paper explores the differences and similarities between social networks and social media in marketing research from the bibliometric perspective and provides a developing trend of their research hotspots in social media and social networks marketing research by keyword co-occurrence analysis and cluster analysis. Additionally, this paper provides some suggestions for firms looking to improve the efficiency of their marketing strategies from social and economic perspectives.

Details

Nankai Business Review International, vol. 12 no. 1
Type: Research Article
ISSN: 2040-8749

Keywords

Article
Publication date: 24 July 2009

Barbara Schultz‐Jones

The purpose of this paper is to review the post‐1996 literature of information science and other disciplines for the application of social network theory and social network

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Abstract

Purpose

The purpose of this paper is to review the post‐1996 literature of information science and other disciplines for the application of social network theory and social network analysis to research that provides an understanding of information environments.

Design/methodology/approach

The literature review involved a content analysis of 373 articles retrieved from five electronic journal databases offering broad disciplinary coverage, and a selection of nine peer‐reviewed electronic access journals in information science. Each database was limited to academic or peer reviewed journals and searched using two query phrases: social network theory (SNT) and social network analysis (SNA).

Findings

The paper demonstrates the growth of interest by information science and other disciplines in research that applies social network theory and utilizes social network analysis, indicating what research approaches and major focus trends differentiate the disciplines.

Research limitations/implications

The search phrases overlook articles using social networks as the only key phrase for indexing. However, the intention was to examine the application of a theoretical concept and specific methodology, so the terms used were appropriate for this purpose.

Practical implications

The paper identifies opportunities to apply social network theory and social network analysis to the study of the exchange of information resources.

Originality/value

The paper demonstrates that information science could advance valuable contributions to an understanding of information behavior using social network theory and social network analysis as a vehicle to connect with a significant body of existing research in other disciplines.

Details

Journal of Documentation, vol. 65 no. 4
Type: Research Article
ISSN: 0022-0418

Keywords

Open Access
Article
Publication date: 22 November 2019

Charles Kirschbaum

Network analysis is a well consolidated research area in several disciplines. Within management and organizational studies, network scholars consolidated a set of research…

1506

Abstract

Purpose

Network analysis is a well consolidated research area in several disciplines. Within management and organizational studies, network scholars consolidated a set of research practices that allowed ease of data collection, high inter case comparability, establishment of nomological laws and commitment to social capital motivation. This paper aims to elicit the criticism it has received and highlight the unsettled lacunae.

Design/methodology/approach

This paper sheds light on Network Analysis’s breakthroughs, while showing how its scholars innovated by responding to critics, and identifying outstanding debates.

Findings

The paper identifies and discusses three streams of criticism that are still outstanding: the role of human agency, the meaning of social ties and the treatment of temporality.

Originality/value

This paper brings to fore current debates within the Network Analysis community, highlighting areas where future studies might contribute.

Details

RAUSP Management Journal, vol. 54 no. 4
Type: Research Article
ISSN: 2531-0488

Keywords

Article
Publication date: 4 May 2020

Fatma Altuntas and Mehmet Şahin Gök

The purpose of this paper is to analyze the wind energy technologies using the social network analysis based on patent information. Analysis of patent documents with social

Abstract

Purpose

The purpose of this paper is to analyze the wind energy technologies using the social network analysis based on patent information. Analysis of patent documents with social network analysis is used to identify the most influential and connected technologies in the field of wind energy.

Design/methodology/approach

In the literature, patent data are often used to evaluate technologies. Patents related to wind energy technologies are obtained from the United States Patent and Trademark Office database and the relationships among sub-technologies based on Corporate Patent Classification (CPC) codes are analyzed in this study. The results of two-phase algorithm for mining high average-utility itemsets algorithm, which is one of the utility mining algorithm in data mining, is used to find associations among wind energy technologies for social network analysis.

Findings

The results of this study show that it is very important to focus on wind motors and technologies related to energy conversion or management systems reducing greenhouse gas emissions. The results of this study imply that Y02E, F03D and F05B CPC codes are the most influential CPC codes based on social network analysis.

Originality/value

Analysis of patent documents with social network analysis for technology evaluation is extremely limited in the literature. There is no research related to the analysis of patent documents with social network analysis, in particular CPC codes, for wind energy technology. This paper fills this gap in the literature. This study explores technologies related to wind energy technologies and identifies the most influential wind energy technologies in practice. This study also extracts useful information and knowledge to identify core corporate patent class (es) in the field of wind energy technology.

Details

Kybernetes, vol. 50 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 3 January 2020

Yuxian Gao

The purpose of this paper is to apply link prediction to community mining and to clarify the role of link prediction in improving the performance of social network analysis.

Abstract

Purpose

The purpose of this paper is to apply link prediction to community mining and to clarify the role of link prediction in improving the performance of social network analysis.

Design/methodology/approach

In this study, the 2009 version of Enron e-mail data set provided by Carnegie Mellon University was selected as the research object first, and bibliometric analysis method and citation analysis method were adopted to compare the differences between various studies. Second, based on the impact of various interpersonal relationships, the link model was adopted to analyze the relationship among people. Finally, the factorization of the matrix was further adopted to obtain the characteristics of the research object, so as to predict the unknown relationship.

Findings

The experimental results show that the prediction results obtained by considering multiple relationships are more accurate than those obtained by considering only one relationship.

Research limitations/implications

Due to the limited number of objects in the data set, the link prediction method has not been tested on the large-scale data set, and the validity and correctness of the method need to be further verified with larger data. In addition, the research on algorithm complexity and algorithm optimization, including the storage of sparse matrix, also need to be further studied. At the same time, in the case of extremely sparse data, the accuracy of the link prediction method will decline a lot, and further research and discussion should be carried out on the sparse data.

Practical implications

The focus of this research is on link prediction in social network analysis. The traditional prediction model is based on a certain relationship between the objects to predict and analyze, but in real life, the relationship between people is diverse, and different relationships are interactive. Therefore, in this study, the graph model is used to express different kinds of relations, and the influence between different kinds of relations is considered in the actual prediction process. Finally, experiments on real data sets prove the effectiveness and accuracy of this method. In addition, link prediction, as an important part of social network analysis, is also of great significance for other applications of social network analysis. This study attempts to prove that link prediction is helpful to the improvement of performance analysis of social network by applying link prediction to community mining.

Originality/value

This study adopts a variety of methods, such as link prediction, data mining, literature analysis and citation analysis. The research direction is relatively new, and the experimental results obtained have a certain degree of credibility, which is of certain reference value for the following related research.

Details

Library Hi Tech, vol. 38 no. 2
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 1 February 2011

Derek L. Hansen

The purpose of this paper is to demonstrate novel techniques for exploring relationship data extracted from social media sites for actionable insights by educators

12315

Abstract

Purpose

The purpose of this paper is to demonstrate novel techniques for exploring relationship data extracted from social media sites for actionable insights by educators, researchers, and administrators.

Design/methodology/approach

The paper demonstrates how non‐programmers can use NodeXL, an open source social network analysis tool built into Excel 2007/2010, to collect, analyze, and visualize network data from social media sites like Twitter and YouTube.

Findings

Researchers and education professionals can use NodeXL to explore (a) social networks to identify important individuals and subgroups, as well as (b) content networks to map the underlying structure of a domain and find important content. Illustrative examples are provided using NodeXL to examine followers of a Twitter user focused on open education, as well as a content network of YouTube videos about surgery.

Research limitations/implications

Tools like NodeXL are making network analysis accessible to non‐technical researchers in a variety of fields spanning the sciences, social sciences, and the humanities. Despite their value, network analysis techniques are only as good as the data that underlie them, requiring careful assessment of possible selection biases and triangulation of findings.

Practical implications

Educational institutions and educators can benefit from more systematically analyzing their social media initiatives from a network perspective.

Originality/value

This paper describes some of the techniques and tools needed to make sense of the social relationships that underlie social media sites. As relational data are increasingly made public, such techniques will enable more systematic analysis by researchers studying social phenomena and practitioners implementing social media initiatives.

Details

On the Horizon, vol. 19 no. 1
Type: Research Article
ISSN: 1074-8121

Keywords

Article
Publication date: 6 July 2022

Xin Xia and Pengcheng Xiang

Managers of megaprojects face social risk management challenges throughout the various design, construction, and operation stages, owing to the various conflicts of…

Abstract

Purpose

Managers of megaprojects face social risk management challenges throughout the various design, construction, and operation stages, owing to the various conflicts of interest among stakeholders, public skepticism, and opposition. However, most existing studies have not focused on the dynamic analysis of integrating social risks in these stages. This study developed a dynamic analysis approach to explore the dynamics of critical social risk factors and related stakeholders of megaprojects and built the managerial maps for various stakeholders.

Design/methodology/approach

Based on the social analysis network (SNA), a dynamic network analysis approach for understanding the dynamics of social risk and related stakeholders has been developed by literature and case analysis. The approach comprises the following steps: (1) generating social risk–stakeholder networks in different stages; (2) analysis of the critical stakeholders and social risk factors; (3) dynamic analysis of social risk factors; and (4) developing social risk management maps for various stakeholders. To verify the feasibility and effectiveness of the approach, 40 megaprojects from China were analyzed.

Findings

According to the results, the local government is a critical stakeholder during all stages, inadequate information promotion (IIP) and imperfect communication and coordination mechanism (ICCM) are key social risk sources throughout the megaproject life cycle. Furthermore, the management maps for government organizations, project implementation groups, and external stakeholders were constructed.

Originality/value

This research has three contributions. First, a dynamic analysis approach of stakeholder-associated social risks in megaprojects is developed, which enriches the social risk management theory of megaprojects and provides inspiration for future research focus. Second, the social risk–stakeholder networks and critical social risks in different stages are confirmed to provide a more valid and accurate picture of social risk management in megaprojects. Third, the social risk managerial maps for different stakeholders built in this research will be beneficial for governments, project implementation groups, and external stakeholders to optimize management strategies.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 19 January 2021

Chih-Ming Chen, Chung Chang and Yung-Ting Chen

Digital humanities aim to use a digital-based revolutionary new way to carry out enhanced forms of humanities research more effectively and efficiently. This study…

Abstract

Purpose

Digital humanities aim to use a digital-based revolutionary new way to carry out enhanced forms of humanities research more effectively and efficiently. This study develops a character social network relationship map tool (CSNRMT) that can semi-automatically assist digital humanists through human-computer interaction to more efficiently and accurately explore the character social network relationships from Chinese ancient texts for useful research findings.

Design/methodology/approach

With a counterbalanced design, semi-structured in-depth interview, and lag sequential analysis, a total of 21 research subjects participated in an experiment to examine the system effectiveness and technology acceptance of adopting the ancient book digital humanities research platform with and without the CSNRMT to interpret the characters and character social network relationships.

Findings

The experimental results reveal that the experimental group with the CSNRMT support appears higher system effectiveness on the interpretation of characters and character social network relationships than the control group without the CSNRMT, but does not achieve a statistically significant difference. Encouragingly, the experimental group with the CSNRMT support presents remarkably higher technology acceptance than the control group without the CSNRMT. Furthermore, use behaviors analyzed by lag sequential analysis reveal that the CSNRMT could assist digital humanists in the interpretation of character social network relationships. The results of the interview present positive opinions on the integration of system interface, smoothness of operation, and external search function.

Research limitations/implications

Currently, the system effectiveness of exploring the character social network relationships from texts for useful research findings by using the CSNRMT developed in this study will be significantly affected by the accuracy of recognizing character names and character social network relationships from Chinese ancient texts. The developed CSNRMT will be more practical when the offered information about character names and character social network relationships is more accurate and broad.

Practical implications

This study develops an ancient book digital humanities research platform with an emerging CSNRMT that provides an easy-to-use real-time interaction interface to semi-automatically support digital humanists to perform digital humanities research with the need of exploring character social network relationships.

Originality/value

At present, a real-time social network analysis tool to provide a friendly interaction interface and effectively assist digital humanists in the digital humanities research with character social networks analysis is still lacked. This study thus presents the CSNRMT that can semi-automatically identify character names from Chinese ancient texts and provide an easy-to-use real-time interaction interface for supporting digital humanities research so that digital humanists could more efficiently and accurately establish character social network relationships from the analyzed texts to explore complicated character social networks relationship and find out useful research findings.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Abstract

Details

The Strategically Networked Organization
Type: Book
ISBN: 978-1-78635-292-7

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