scholarly journals Social network analysis and festival cities: an exploration of concepts, literature and methods

2014 ◽  
Vol 5 (3) ◽  
pp. 311-322 ◽  
Author(s):  
David Jarman ◽  
Eleni Theodoraki ◽  
Hazel Hall ◽  
Jane Ali-Knight
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Design Methodology ◽  
Dynamic Environments ◽  
Diverse Range ◽  
Content Type ◽  
Secondary Material ◽  
Tourism Studies ◽  
History Of

Purpose – Social network analysis (SNA) is an under-utilised framework for research into festivals and events. The purpose of this paper is to reflect on the history of SNA and explore its key concepts, in order that they might be applied to festivals and their environments. Design/methodology/approach – Secondary material underpins the paper, primarily SNA literature, tourism studies research and festival industry publications. Findings – Festival cities offer dynamic environments in which to investigate the workings of social networks. The importance of such networks has long been recognised within the industry, yet there is scant reflection of this in the event studies literature. Uses of SNA in tourism studies publications offer some precedents. Originality/value – This paper emphasises the importance of relationships between people in a festival economy, complementing and building upon stakeholder analyses. A research method is proposed, suitable for application across a diverse range of festivals and events.

Filling structural holes? Guanxi-based facilitation of knowledge sharing within a destination network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiayuan Liu ◽  
Jianzhou Yan
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Knowledge Sharing ◽  
Design Methodology ◽  
Network Structures ◽  
Structured Interviews ◽  
Tourist Destination ◽  
Structural Holes ◽  
Content Type

PurposeThis study examines the relationships between structural holes, guanxi and knowledge sharing among groups of stakeholders within a Chinese destination network.Design/methodology/approachThis study conducted surveys, social network analysis and semi-structured interviews to gather data from the stakeholders of a popular Chinese tourist destination to test its hypotheses.FindingsKnowledge sharing within the destination network was impeded by structural holes but facilitated by guanxi. Furthermore, the impeding effect of structural holes on knowledge sharing is alleviated by guanxi.Originality/valueThis study illustrates the ways that stakeholders exploit structural holes and guanxi to promote knowledge sharing, and thus offers novel insights into how destination network structures affect the efficacy of stakeholders when it comes to sharing knowledge and promoting their destination.

scholarly journals Polarisation in political Twitter conversations

2014 ◽  
Vol 66 (3) ◽  
pp. 329-341 ◽  
Author(s):  
David Gunnarsson Lorentzen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Design Methodology ◽  
Right Wing ◽  
Content Type ◽  
The Social ◽  
Left Block ◽  
The Right

Purpose – The purpose of this paper is to describe and analyse relationships and communication between Twitter actors in Swedish political conversations. More specifically, the paper aims to identify the most prominent actors, among these actors identify the sub-groups of actors with similar political affiliations, and describe and analyse the relationships and communication between these sub-groups. Design/methodology/approach – Data were collected during four weeks in September 2012, using Twitter API. The material included 77,436 tweets from 10,294 Twitter actors containing the hashtag #svpol. In total, 916 prominent actors were identified and categorised according to the main political blocks, using information from their profiles. Social network analysis was utilised to map the relationships and the communication between these actors. Findings – There was a marked dominance of the three main political blocks among the 916 most prominent actors: left block, centre-right block, and right-wing block. The results from the social network analysis suggest that while polarisation exists in both followership and re-tweet networks, actors follow and re-tweet actors from other groups. The mention network did not show any signs of polarisation. The blocks differed from each other with the right-wingers being tighter and far more active, but also more distant from the others in the followership network. Originality/value – While a few papers have studied political polarisation on Twitter, this is the first to study the phenomenon using followership data, mention data, and re-tweet data.

scholarly journals Understanding governance in the implementation of rainwater systems in the Amazon – Belem

2020 ◽  
Vol 31 (1) ◽  
pp. 54-74
Author(s):  
Pedro Pablo Cardoso Castro ◽  
Nirvia Ravena ◽  
Ronaldo Mendes
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Process Planning ◽  
Design Methodology ◽  
Decision Making Process ◽  
Content Type ◽  
Key Players

Purpose The purpose of this paper is to develop a case study of niche governance to analyze the governance of rainwater systems in the Amazon. Design/methodology/approach A visualization of the interactions of stakeholders was made with the use of social network analysis, where data were collected through interviews to experts from the region. A framework based on niche management and the safe, resilient and sustainable (Safe and SuRe) principles were used to interpret the results. Findings The work identifies key players and issues influencing governance for the implementation of rainwater systems; and capture of decision-making powers by agents making evident redundancies in the management of rainwater in the region; highlighting issues of lack of inclusion in the decision-making process, planning and implementation; threatening the sustainability, resilience and governance of rainwater systems in Belem. Originality/value Methodologically, this work is the first of its kind for the amazon and contributes to the exploration of tools and frameworks to assess governance in the implementation of rainwater systems.

Broadcasting, reacting, engaging – three strategies for CSR communication in Twitter

2014 ◽  
Vol 18 (4) ◽  
pp. 322-342 ◽  
Author(s):  
Michael Etter
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Public Relations ◽  
Design Methodology ◽  
Relationship Building ◽  
Content Type ◽  
Csr Communication ◽  
The Social

Purpose – Symmetric communication and relationship building are core principles of public relations, which have been highlighted for CSR communication. The purpose of this paper is to develop three different communication strategies for CSR communication in Twitter, of which each contributes differently to the ideals of symmetric communication and relationship building. The framework is then applied to analyze how companies use the micro-blogging service Twitter for CSR communication. Design/methodology/approach – Social network analysis is used to identify the 30 most central corporate accounts in a CSR Twitter network. Findings – From the social network analysis 40,000 tweets are extracted and manually coded. Anova is applied to investigate differences in the weighting of CSR topics between the different strategies. Originality/value – So far not much is known about how social media, such as Twitter, contribute to the core principles of public relations, if companies use social media to foster symmetric communication and relationship management, or which CSR topics they address.

Social network analysis applications in sustainable construction and built environment management: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Built Environment ◽  
Methodological Approach ◽  
Relevant Literature ◽  
Sustainable Construction ◽  
Centrality Measures ◽  
Environment Management ◽  
Content Type

PurposeApplications of social network analysis (SNA) are evidently popular amongst scholars for mapping stakeholder and other relational networks in improving the sustainability of construction activities and the resulting built environment. Nevertheless, the literature reveals a lack of thorough understanding of optimal SNA applications in this field. Therefore, this paper aims to convey a comprehensive critical review of past applications of SNA in this field.Design/methodology/approach95 relevant journal papers were initially identified from the “Web of Science” database and a bibliometric analysis was carried out using the “VOS Viewer” software. The subsequent in-depth review of the SNA methods, focussed on 24 specifically relevant papers selected from these aforesaid 95 papers.FindingsA significant growth of publications in this field was identified after 2014, especially related to topics on stakeholder management. “Journal of Cleaner Production”, “International Journal of Project Management” and “Sustainability” were identified as the most productive sources in this field, with the majority of publications from China. Interviews and questionnaires were the popular data collection methods while SNA “Centrality” measures were utilised in over 70% of the studies. Furthermore, potential areas were noted, to improve the mapping and thereby provide useful information to managers who could influence relevant networks and consequentially better sustainability outcomes, including those enhanced by collaborative networks.Originality/valueCloser collaboration has been found to help enhance sustainability in construction and built environment, hence attracting research interest amongst scholars on how best to enable this. SNA is established as a significant methodological approach to analysing interrelationships and collaborative potential in general. In a pioneering application here, this paper initiates the drawing together of findings from relevant literature to provide useful insights for future researchers to comprehensively identify, compare and contrast the applications of SNA techniques in construction and built environment management from a sustainability viewpoint.

The evolution of the intellectual structure of strategic management between 1980 and 2019

2020 ◽  
Vol 13 (4) ◽  
pp. 503-534
Author(s):  
Mehmet Ali Köseoğlu ◽  
John Parnell
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Strategic Management ◽  
Citation Analysis ◽  
Intellectual Structure ◽  
Future Directions ◽  
Content Type ◽  
The Social ◽  
Economic Foundation

PurposeThe authors evaluate the evolution of the intellectual structure of strategic management (SM) by employing a document co-citation analysis through a network analysis for academic citations in articles published in the Strategic Management Journal (SMJ).Design/methodology/approachThe authors employed the co-citation analysis through the social network analysis.FindingsThe authors outlined the evolution of the academic foundations of the structure and emphasized several domains. The economic foundation of SM research with macro and micro perspectives has generated a solid knowledge stock in the literature. Industrial organization (IO) psychology has also been another dominant foundation. Its robust development and extension in the literature have focused on cognitive issues in actors' behaviors as a behavioral foundation of SM. Methodological issues in SM research have become dominant between 2004 and 2011, but their influence has been inconsistent. The authors concluded by recommending future directions to increase maturity in the SM research domain.Originality/valueThis is the first paper to elucidate the intellectual structure of SM by adopting the co-citation analysis through the social network analysis.

FinTech innovation and knowledge flows in Hong Kong’s financial sector: a social network analysis approach

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anson Au
Keyword(s):  
Hong Kong ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Commercial Banks ◽  
Financial Sector ◽  
Knowledge Flows ◽  
Foreign Firms ◽  
Content Type ◽  
Network Position

Purpose This paper aims to examine how financial technology (FinTech) knowledge from foreign firms flows into and among elite commercial banks in Hong Kong’s financial sector to drive innovation. Design/methodology/approach Using social network analysis and regression analysis on a novel database of patents held by Hong Kong’s elite commercial banks, this paper examines the relationships between network position and FinTech knowledge flow. Findings This paper finds four untold patterns of innovation and inequality in Hong Kong’s financial sector: only three banks are responsible for all the FinTech knowledge entering Hong Kong; most foreign FinTech comes from the USA through Hong Kong and Shanghai Banking Corporation, whereas most FinTech from China enters through Fubon Bank and Development Bank of Singapore; older banks and banks with more connections to firms inside Asia are more likely to import FinTech; the most beneficial sources of FinTech for a bank’s network position are firms from outside Asia. Originality/value Despite the well-documented volumes of cross-border and cross-continental movement of financial institutions in Hong Kong, there is little work on the knowledge flows that underwrite this mobility. This paper addresses this gap by using FinTech knowledge flows to map the distribution of innovation, network position and competitive advantage in Hong Kong’s financial sector.

Social network analysis and data visualization of MIS international collaboration in Taiwan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ting Chuang ◽  
Yi-Hsi Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Collaboration ◽  
Research Productivity ◽  
Research Collaboration ◽  
Clustering Algorithms ◽  
The United States ◽  
Content Type ◽  
Collaboration Patterns

PurposeThe purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.Design/methodology/approachThe authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.FindingsThe authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.Originality/valueThis study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

Who is the boss? Identifying key roles in telecom fraud network via centrality-guided deep random walk

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Chun Chang ◽  
Kuan-Ting Lai ◽  
Seng-Cho T. Chou ◽  
Wei-Chuan Chiang ◽  
Yuan-Chen Lin
Keyword(s):  
Social Network ◽  
Random Walk ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Random Walks ◽  
Interpersonal Relationships ◽  
Interaction Network ◽  
Data Set ◽  
Content Type ◽  
Structural Equivalence

PurposeTelecommunication (telecom) fraud is one of the most common crimes and causes the greatest financial losses. To effectively eradicate fraud groups, the key fraudsters must be identified and captured. One strategy is to analyze the fraud interaction network using social network analysis. However, the underlying structures of fraud networks are different from those of common social networks, which makes traditional indicators such as centrality not directly applicable. Recently, a new line of research called deep random walk has emerged. These methods utilize random walks to explore local information and then apply deep learning algorithms to learn the representative feature vectors. Although effective for many types of networks, random walk is used for discovering local structural equivalence and does not consider the global properties of nodes.Design/methodology/approachThe authors proposed a new method to combine the merits of deep random walk and social network analysis, which is called centrality-guided deep random walk. By using the centrality of nodes as edge weights, the authors’ biased random walks implicitly consider the global importance of nodes and can thus find key fraudster roles more accurately. To evaluate the authors’ algorithm, a real telecom fraud data set with around 562 fraudsters was built, which is the largest telecom fraud network to date.FindingsThe authors’ proposed method achieved better results than traditional centrality indices and various deep random walk algorithms and successfully identified key roles in a fraud network.Research limitations/implicationsThe study used co-offending and flight record to construct a criminal network, more interpersonal relationships of fraudsters, such as friendships and relatives, can be included in the future.Originality/valueThis paper proposed a novel algorithm, centrality-guided deep random walk, and applied it to a new telecom fraud data set. Experimental results show that the authors’ method can successfully identify the key roles in a fraud group and outperform other baseline methods. To the best of the authors’ knowledge, it is the largest analysis of telecom fraud network to date.

Obstacles and opportunities for networked practice: a social network analysis of an inter-organizational STEM ecosystem

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yi-Hwa Liou ◽  
Alan J. Daly
Keyword(s):  
Higher Education ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Geographic Region ◽  
Central Position ◽  
Content Type ◽  
Related Information ◽  
Stem Pipeline ◽  
And Mathematics

PurposeThis study responds to major administrative and policy priorities to support science, technology, engineering and mathematics (STEM) education by investigating a multi-sector ecosystem of regional organizations that support a STEM pipeline for education and careers.Design/methodology/approachWe use social network analysis to investigate an entire region within a geographic region of California which included 316 organizations that represent different stakeholder groups, including educational institutions (school districts, schools and higher education), government, private companies, museums, libraries and multiple community-based organizations. This STEM ecosystem reflects a systems-level analysis of a region from a unique social network perspective.FindingsResults indicate that organizations have a surface-level access to STEM-related information, but the deeper and more intense relationship which involves strategic collaboration is limited. Further, interactions around information and collaboration between organizations were purportedly in part to be about education, rarely included PK-12 schools and district as central actors in the ecosystem. In addition, while institutions of higher education occupy a central position in connecting and bridging organizations within the ecosystem, higher education's connectivity to the PK-12 education sector is relatively limited in terms of building research and practice partnerships.Originality/valueThis research has implications for how regional-level complex systems are analyzed, led and catalyzed and further reflects the need to intentionally attend to the growth of STEM networks.

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