Social Network Analysis

11 Key excerpts on "Social Network Analysis"

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  Methodological Approaches for Workplace Research and Management

  • Chiara Tagliaro, Marko Orel, Ying Hua, Chiara Tagliaro, Marko Orel, Ying Hua(Authors)
  • 2023(Publication Date)
  • Routledge

    (Publisher)

  10 Social Network Analysis Studying social interactions and relations in the workplace Yaoyi Zhou Virginia Tech, USA

  DOI: 10.1201/9781003289845-10

  This chapter has been made available under a CC-BY-NC-ND 4.0 license.

  10.1 Background

  Social networks are defined as a set of nodes (or network members) that are tied by one or more types of relations (Wasserman & Faust, 1994 ). For those not familiar with network research, a network is a set of actors connected by a set of ties. The actors (often called “nodes”) can be persons, teams, organizations, concepts, etc. Ties connect pairs of actors and can be directed (i.e., send a message to someone) or undirected (as in being physically proximate) or valued (i.e., strong vs. weak friendship). A set of ties of a given type (such as friendship ties) constitutes a binary social relation, and each relation defines a different network (e.g., the friendship network is distinct from the advice network). Different kinds of ties are typically assumed to function differently, although empirically they might be correlated. Some typical phenomena such as small-world effect (Pool & Kochen, 1978 ), the strength of weak ties (Granovetter, 1983 ), and many others may be observed in social networks.

  Social Network Analysis (SNA) is a research methodology that seeks to identify underlying patterns of social relations based on the way actors are connected with each other (Breiger, 2004 ; Scott & Carrington, 2011 ). The unit of analysis in SNA is not the individual, but the relationships or interactions that occur between members of the network. Using SNA, the social environment can be mapped as patterns of relationships among interacting members.

  When applying a network perspective, SNA can be used to indicate how a certain individual is connected to others, and also indicates the cohesion of a network. There are two key indicators used in SNA: “density” and “centrality.” Density provides a measure of the overall “connections” between the participants. The more participants connected to one another (by, for example, their message exchanges), the higher will be the density value of the network. While centrality indicates the extent to which an individual was connected to other actors within a network (Wasserman & Faust, 1994

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  Social Network Analysis in Construction

  • Stephen Pryke(Author)
  • 2012(Publication Date)
  • Wiley-Blackwell

    (Publisher)

  coalition of firms (Winch, 1989) with some means of useful analysis of such systems. The chapter will provide a very brief history of the development of SNA; it will summarise the limitations inherent in other methods and will provide an introduction to SNA terminology. Some examples of the type of data that might be usefully analysed using SNA will be discussed and there will be a summary of the available software for social network analysts. Finally, some further reading and a bibliography are provided for those wishing to start using SNA.

  Definition

  Social Network Analysis involves the representation of organisational relationships as a system of nodes or actors linked by precisely classified connections, along with the mathematics that defines the structural characteristics of the relationship between the nodes. Wasserman and Faust (1994) define a social network in even simpler terms as:

  a finite set or sets of actors and the relation or relations [between them].

  Research into the activities, and the effectiveness of such activities, in construction-related projects has in the past frequently relied upon what might be regarded as positivist approaches. Although viewed by some as robust, these approaches try to explain what comprises a complex social arrangement (Morris, 1994) through methods that essentially have their origins in natural science (Pryke, 2004b). Project management researchers have increasingly looked to the social science disciplines to explain and understand the key issues and problems faced in the management of construction (and non-construction) projects (Bresnen et al ., 2005). Some have argued for a need to bridge positivist and interpretivist approaches with more qualitative methods (Chih Lin, 1998), and Loosemore (1998) has argued that SNA is a quantitative tool capable of being applied within an interpretive context in construction research. Loosemore questions the association of quantitative and qualitative methods with causality and the production of universal models, but feels that both quantitative and qualitative methods (jointly) have a part to play in understanding social roles, positions and behaviour in the construction project environment. Others have argued that qualitative and quantitative approaches can be integrated using critical realism (Smyth et al

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  Social Network Analysis and Egyptology

  • Danijela Stefanović(Author)
  • 2024(Publication Date)
  • Routledge

    (Publisher)

  2 Social Network Analysis – a brief overview

  DOI: 10.4324/9781003457015-2

  Social Network Analysis (SNA) is a method developed in the mid-XX century in mathematics, anthropology, and sociology, and is used to describe, analyse, and measure human relations.1 However, its roots can be traced back to the end of the XIX century and research on social structures and social links by Émile Durkheim and Ferdinand Tönnies.2 The works of Jacob Moreno, William Lloyd Warner, and Elton Mayo, as well as of Alfred Radcliffe-Brown, exemplifying the three leading traditions in network studies, marked the early decades of the XX century.3

  Jacob Moreno is particularly important among these scholars. Along with Helen Hall Jennings he developed sociometry, a technique obtained by applying quantitative methods that inquire into the development and organisation of individual groups and the position of single actors within them.4 His major achievement was the invention of a sociogram as a way to represent the formal properties of social configurations. The sociogram has become one of the most powerful innovations in network analysis, because it enables the visualisation of social networks.

  With Alfred Radcliffe-Brown’s stress on the concept of ‘social structure,’ and the idea that social actions were organised, studies of social networks came to the fore.5 In the 1960s and the 1970s, a significant number of researchers worked on the implementation of various theories and concepts for the study of social interactions and connections, leading to Social Network Analysis. For example, Stanley Milgram developed the concept of ‘six degrees of separation,’ and Mark Granovetter elaborated on the theory of the ‘strength of weak ties’ within the network.6 Since then, the body of research on Social Network Analysis has grown significantly, and academic journals, textbooks, vocabulary, and an increasing sophistication in its technical tools have been developed.7

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  The Strategically Networked Organization

  Leveraging Social Networks to Improve Organizational Performance

  • Hanna Lehtimaki(Author)
  • 2016(Publication Date)
  • Emerald Group Publishing Limited

    (Publisher)

  3 ▾ Social Network Analysis for Strategically Networked Organization KEY CONTENTS IN THIS CHAPTER Introduction to Social Network Analysis measures and conducting a social network survey. Ethical considerations of using Social Network Analysis to help managers make use of social networks in strategy making. A brief review of network visualization tools. Examining strategy practice as embedded in the relational context within the firm directs attention to the social relations between individuals. Social Network Analysis allow for examining how organizing and strategizing coevolve. Social Network Analysis seeks to understand the social constraints and opportunities for individual behavior in organizational settings ( Borgatti & Foster, 2003 , p. 1000). It shifts the focus from organization and design of organizational structures to processes and people. What becomes 35 of interest is how people work together, what is the operational dynamics in the organization, and what is it that people do in their daily work when communicating and collaborating with each other. The point here is that in order for us to understand and appreciate the dynamics that result in an organization structure or a documented strategy of a company, we need to change the vocabulary with which we talk about organization and strategy. Talking about organizing and strategizing directs atten-tion to the activities, relationships, and people who make things happen. It also directs attention to the informal organization and the social relationships between members of the organization. The usefulness of Social Network Analysis in strategy making is in bringing to the forefront the social connections between mem-bers of the organization, and the ways by which social relations and a structure of social relationships shape strategy making. Social networks can be studied as networks of one person, the ego networks, and the network of a group of people, the whole net-works.

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  Social Networks and Music Worlds

  • Nick Crossley, Siobhan McAndrew, Paul Widdop, Nick Crossley, Siobhan McAndrew, Paul Widdop(Authors)
  • 2014(Publication Date)
  • Taylor & Francis

    (Publisher)

  2  What is Social Network Analysis? An introduction for music scholars Nick Crossley, Siobhan McAndrew and Paul Widdop

  In this chapter we offer a brief introduction to the fundamental concepts and techniques of Social Network Analysis (SNA) used by most of the contributors to this book. Our primary aim is to provide readers who are unfamiliar with SNA with the necessary background knowledge to fully engage with the book. Those who wish to go further and use SNA in their own research will need to read more widely. However, we hope that the book will inspire music and culture scholars to consider using SNA and to this end we extend our remit slightly by both discussing some of the questions that SNA allows us to address and briefly introducing some of the main software packages that network analysts typically use: e.g. UCINET,1 Pajek,2 PNet3 and Siena.4

  Readers who wish to learn further about SNA should consult one of the excellent textbooks in the area. We briefly review our preferred teaching texts at the end of the chapter. Networks and network analysis

  As we noted in the Introduction to this book, ‘musicking’ is collective action. It involves connection and interaction between social actors. On a very basic level, for example, individual musicians interact both with one another, with a variety of support personnel, such as promoters, managers and studio engineers, who also interact with one another, and with audiences, who again also interact with one another and with support personnel. In addition, connections exist on other levels: works borrow from other works, the organisations involved in the music industry interlock in different ways and venues, cities, festivals and countries are all linked by the flow of artists and works between them.

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  Handbook of Data Analysis

  • Melissa A Hardy, Alan Bryman, Melissa A Hardy, Alan Bryman(Authors)
  • 2009(Publication Date)
  • SAGE Publications Ltd

    (Publisher)

  The study of social relationships among actors – whether individual human beings or animals of other species, small groups or economic organizations, occupations or social classes, nations or world military alliances – is fundamental to the social sciences. Social Network Analysis may be defined as the disci-plined inquiry into the patterning of relations among social actors, as well as the patterning of relationships among actors at different levels of analysis (such as persons and groups). Following an introduction to data analysis issues in social networks research and to the basic forms of network representation, three broad topics are treated under this chapter’s main headings: types of equivalence, statistical models (emphasizing a new class of logistic regression models for networks), and culture and cognition. Each section emphasizes data-analytic strategies used in exemplary research studies of social networks. Computer pro-grams and related issues are briefly treated at the end of the chapter. FROM METAPHOR TO DATA ANALYSIS Network metaphors have long had great intuitive appeal for social thinkers and social scientists. Writing in 1857, Marx (1956: 96) said that ‘society is not merely an aggregate of individuals; it is the sum of the relations in which these individuals stand to one another’. Thirty-five years later, Durkheim, in his Latin thesis, traced his interest in social morphology to that of the eighteenth-century thinker Montesquieu, who had identified various types of society, such as monarchy, aristocracy, and republic, ‘not on the basis of division of labor or the nature of their social ties, but solely according to the nature of their sovereign authority’, and Durkheim went on to criticize this strategy as a failure to see ‘that the essential is not the number of persons subject to the same authority, but the number bound by some form of relationship’ (Durkheim, 1965: 32, 38).

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  Exploratory Social Network Analysis with Pajek

  Revised and Expanded Edition for Updated Software

  • Wouter De Nooy, Andrej Mrvar, Vladimir Batagelj(Authors)
  • 2018(Publication Date)
  • Cambridge University Press

    (Publisher)

  Part I Fundamentals Social Network Analysis focuses on ties among, for example, people, groups of people, organizations, and countries. These ties combine to form networks, which we will learn to analyze. The first part of this book introduces the concept of a social network. We discuss several types of net- works and the ways in which we can analyze them numerically and visu- ally with the computer software program Pajek, which is used throughout this book. After studying Chapters 1 and 2, you should understand the concept of a social network and be able to create, manipulate, and visu- alize a social network with the software presented in this book. 1 1 Looking for Social Structure 1.1 Introduction The social sciences focus on structure: the structure of human groups, communities, organizations, markets, society, or the world system. In this book, we conceptualize social structure as a network of social ties. Social network analysts assume that interpersonal ties matter, as do ties among organizations or countries, because they transmit behavior, atti- tudes, information, or goods. Social Network Analysis offers the method- ology to analyze social relations; it tells us how to conceptualize social networks and how to analyze them. In this book, we present the most important methods of exploring social networks, emphasizing visual exploration. Network visualization has been an important tool for researchers from the very beginning of Social Network Analysis. This chapter introduces the basic elements of a social network and shows how to construct and draw a social network. 1.2 Sociometry and Sociogram The basis of social network visualization was laid by researchers who called themselves sociometrists. Their leader, J. L. Moreno, founded a social science called sociometry, which studies interpersonal relations. Society, they argued, is not an aggregate of individuals and their char- acteristics, as statisticians assume, but a structure of interpersonal ties.

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  Food Systems Modelling

  Tools for Assessing Sustainability in Food and Agriculture

  • Christian J. Peters, Dawn D. Thilmany, Dawn Thilmany(Authors)
  • 2022(Publication Date)
  • Academic Press

    (Publisher)

  Other studies utilize mixed methods sequentially, such as beginning with a network analysis and conducting qualitative interviews to investigate underlying influences that impact network connectivity (Luxton and Sbicca, 2021 ; Rocker, 2019). Some researchers have expressed the suggestion that SNA and Input-Output analysis could be seen as complementary methods, articulating multiple levels and dimensions of food systems phenomena from the economic sector level to the individuals, organizations and businesses (Goldenberg and Meter, 2019 ; Trivette, 2019). Future opportunities for multi-level systems research could be approached by interdisciplinary research teams to more deeply explore connections between sector-level economic data with individual and organizational level relational dynamics, as well as subjective accounts of particular practices and activities. 11.7 Conclusion In this chapter, we have explained foundational concepts and methodological approaches in Social Network Analysis, with particular attention to contexts in which SNA has been applied in existing food systems research. Throughout we have sought to offer ideas and open pathways for possible future uses of SNA in food systems research. We have identified some common characteristics of food systems research that has integrated SNA to date and we have highlighted the common patterns found in these early studies, as well as gaps and opportunities for ways that SNA could be integrated in future research design. We have also identified several possible research design ideas, as well as instruments and tools for data collection, analysis and visualization. Food systems studies at their core address the complex interactions of both coordination and contestation among people and resources through production, trade, and consumption as mediated by diverse influences including policy, funding, cultural and social practices, institutional structures, and much more

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  The SAGE Handbook of Sociolinguistics

  • Ruth Wodak, Barbara Johnstone, Paul E Kerswill, Ruth Wodak, Barbara Johnstone, Paul E Kerswill(Authors)
  • 2010(Publication Date)
  • SAGE Publications Ltd

    (Publisher)

  Secondly, network analysis has been spread over a large geographic area through its own scientific networks: In 1979 Barry Wellman founded the International Network of Social Network Analysts (INSNA, http://www.insna.org/), which, alongside its other responsibilities, is in charge of the organization of an annual conference, the International Sunbelt Social Network Conference. The network community has also produced scholarly journals, such as Connections (founded by Barry Wellman), Social Networks (founded by Lin Freeman) and Social Structure (founded by David Krackhardt). Network analysis is thus influenced by different research clusters, which becomes evident through the growing interest in social networks since 1990 (Wasserman et al., Social Network E v a V e t t e r SOCIAL NETWORK 209 2005: 1) and the considerable technical and formal sophistication associated with this growth (Wasserman and Faust, 1994; Scott, 2000; Freeman, 2004; Carrington et al., 2005; Marsden, 2005; Jansen, 2006). Thirdly and most important, although structural analysis probably constitutes the most prominent branch of the networks perspective, it cannot cover the heterogeneity of this scientific area. An example for this dilemma is network research outside the English-speaking world, in particular the research conducted by Michel Forsé and his peers in France (Degenne and Forsé, 1994 [2004]; Forsé and Langlois, 1997; Forsé 2002; Mercklé, 2004; Forsé, 2008). These researchers in their structural interactionism the network approach combines with the theory of rational choice in the broader sense. Concurrently, German-language net-work researchers are trying to sound out the poten-tial of qualitative data collection and analysis of networks in different research areas, for example biographical research, literature and politics (see e.g. Hollstein and Straus, 2006).

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  Handbook of Graph Drawing and Visualization

  • Roberto Tamassia(Author)
  • 2013(Publication Date)
  • Chapman and Hall/CRC

    (Publisher)

  26 Social Networks Ulrik Brandes University of Konstanz Linton C. Freeman University of California, Irvine Dorothea Wagner Karlsruhe Institute of Technology 26.1 Social Network Analysis ................................... 805 26.2 Visualization Principles ................................... 807 Illustrative Example • Substance, Design, Algorithm 26.3 Substance-Based Designs .................................. 810 Prominence • Cohesion • Two-Mode Networks • Dynamics 26.4 Trends and Challenges ..................................... 827 References .......................................................... 828 Social networks provide a rich source of graph drawing problems, because they appear in an incredibly wide variety of forms and contexts. After sketching the scope of Social Network Analysis, we establish some general principles for social network visualization before finally reviewing applications of, and challenges for, graph drawing methods in this area. Other accounts more generally relating to the status of visualization in Social Network Analysis are given, e.g., in [Klo81, BKR + 99, Fre00, Fre05, BKR06]. Surveys that are more comprehensive on information visualization approaches, interaction, and network applications from social media are given in [CM11, RF10, CY10]. 26.1 Social Network Analysis The fundamental assumption underlying social network theory is the idea that seemingly autonomous individuals and organizations are in fact embedded in social relations and interactions [BMBL09]. The term social network was coined to delineate the relational perspective from other research traditions on social groups and social categories [Bar54]. In general, a social network consists of actors (e.g., persons, organizations) and some form of (often, but not necessarily: social) relation among them. The network structure is usually modeled as a graph, in which vertices represent actors, and edges represent ties , i.e., the existence of a relation between two actors.

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  Software Designers in Action

  A Human-Centric Look at Design Work

  • Marian Petre, Andre Van Der Hoek, Marian Petre, Andre Van Der Hoek(Authors)
  • 2013(Publication Date)
  • Chapman and Hall/CRC

    (Publisher)

  363 © 2010 Taylor & Francis Group, LLC C H A P T E R 21 Application of Network Analysis to Conversations of Professional Software Designers An Exploratory Study Sian Joel-Edgar University of Exeter Business School Paul Rodgers Northumbria University 21.1 INTRODUCTION The concept of network analysis “encompasses theories, models, and applications that are expressed in terms of relational concepts or processes. The unit of analysis in network analysis is not the individual, but an entity consisting of a collection of individuals and the linkages” (Wasserman and Faust, 1994). Network analysis looks at the connections between actors and how such connections form into a network. Network analysis helps to interpret group data such as communities of practice. It can identify cliques, trace how CONTENTS 21.1 Introduction 365 21.2 Methodology 367 21.3 Results 369 21.4 Trends 372 21.5 Dominant, Go-Between, and Weaker Objects 372 21.6 Conclusions and Future Work 378 References 379 364 ◾ Software Designers in Action: A Human-Centric Look at Design Work © 2010 Taylor & Francis Group, LLC information flows through networks, and holistically understand what is going on with a connected number of individuals. Network analysis can also be used to test hypotheses for groups or clusters of people; for instance, the idea that boys socialize more with other boys or the idea that people with weak ties are useful for learning about new ideas or jobs (Granovetter, 1973, 1982). In comparison with other types of methodological approaches, network analysis looks at the relational approach rather than at the attribute. It also looks at the structure and the composition of the connections that make a group rather than looking at individuals and their characteristics. In this chapter, we explore the use of network analysis in the understanding of conver-sations.

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