social networking

(noun)

The use of Internet communities to network and communicate using shared interests, related skills, or geographical location between consumers and businesses.

Related Terms

Examples of social networking in the following topics:

  • Social Networks

    • A social network is a social structure that exists between actors—individuals or organizations.
    • Facebook is an example of a large social network.
    • Social networks are composed of nodes and ties.
    • The study of social networks is called either social network analysis or social network theory.
    • Assess the role of social networks in the socialization of people

  • Preface

    • This book began as a set of reading notes as Hanneman sought to teach himself the basics of social network analysis.
    • It then became a set of lecture notes for students in his undergraduate course in social network analysis.
    • Our goal in preparing this book is to provide a very basic introduction to the core ideas of social network analysis, and how these ideas are implemented in the methodologies that many social network analysts use.
    • Social network analysis is a continuously and rapidly evolving field, and is one branch of the broader study of networks and complex systems.
    • The concepts and techniques of social network analysis are informed by, and inform the evolution of these broader fields.

  • Introduction

    • The basic idea of a social network is very simple.
    • A social network is a set of actors (or points, or nodes, or agents) that may have relationships (or edges, or ties) with one another.
    • To build a useful understanding of a social network, a complete and rigorous description of a pattern of social relationships is a necessary starting point for analysis.
    • The amount of information that we need to describe even small social networks can be quite great.
    • All of the tasks of social network methods are made easier by using tools from mathematics.

  • Social Networks

    • A social network is a social structure between actors, connecting them through various social familiarities.
    • A social network is a social structure between actors, either individuals or organizations.
    • The study of social networks is called both "social network analysis" and "social network theory. " Research in a number of academic fields has demonstrated that social networks operate on many levels, from families up to the level of nations, and play a critical role in determining the way problems are solved, organizations are run, and the degree to which individuals succeed in achieving their goals.
    • Social networks are the basic tools used by individuals to meet other people, recreate, and to find social support.
    • Social network theory views social relationships in terms of nodes and ties.

  • Networks

    • A social network is a social structure between actors, either individuals or organizations.
    • The study of social networks is called both social network analysis and social network theory.
    • Social network theory views social relationships in terms of nodes and ties.
    • The shape of the social network helps determine a network's usefulness to its individuals.
    • Similarly, individuals can exercise influence or act as brokers within their social networks by bridging two networks that are not directly linked (called filling social holes).

  • Introduction: Applying statistical tools to network data

    • A very large part of social network methodology, consequently, deals with relatively small networks, networks where we have confidence in the reliability of our observations about the relations among the actors.
    • Most of the tools of social network analysis involve the use of mathematical functions to describe networks and their sub-structures.
    • In more recent work, however, some of the focus of social network research has moved away from these roots.
    • Increasingly, the social networks that are being studied may contain many nodes; and, sometimes our observations about these very large networks are based not on censuses, but on samples of nodes.
    • Inferential statistics have also proven to have very useful applications to social network analysis.

  • Bibliography

    • "Graph theory in network analysis" Social Networks 5: 235-244.
    • Social structures: A network approach.
    • Social structures: A network approach.
    • A graph theoretic blocking procedure for social networks, Social Networks, 4: 147-167
    • Centrality in social networks: Conceptual clarification, Social Networks, 1: 215-39.

  • Introduction: Representing networks with graphs

    • Social network analysts use two kinds of tools from mathematics to represent information about patterns of ties among social actors: graphs and matrices.
    • On this page, we we will learn enough about graphs to understand how to represent social network data.
    • On the next page, we will look at matrix representations of social relations.
    • With these tools in hand, we can understand most of the things that network analysts do with such data (for example, calculate precise measures of "relative density of ties").
    • There is a lot more to these topics than we will cover here; mathematics has whole sub-fields devoted to "graph theory" and to "matrix algebra. " Social scientists have borrowed just a few things that they find helpful for describing and analyzing patterns of social relations.

  • Modality and levels of analysis

    • Often these networks of interpersonal relations become "social facts" and take on a life of their own.
    • Most social network analysts think of individual persons as being embedded in networks that are embedded in networks that are embedded in networks.
    • A data set that contains information about two types of social entities (say persons and organizations) is a two mode network.
    • Of course, this kind of view of the nature of social structures is not unique to social network analyst.
    • Having claimed that social network methods are particularly well suited for dealing with multiple levels of analysis and multi-modal data structures, it must immediately be admitted that social network analysis rarely actually takes much advantage.

  • Summary

    • But, there is still a good bit more, as the application of statistical modeling to network data is one of the "leading edges" of the field of social (and other) network analyses.
    • First, for very large networks, methods for finding and describing the distributions of network features provide important tools for understanding the likely patterns of behavior of the whole network and the actors embedded in it.
    • Second, we have increasingly come to realize that the relations we see among actors in a network at a point in time are best seen as probabilistic ("stochastic") outcomes of underlying processes of evolution of networks, and probabilistic actions of actors embedded in those networks.
    • Taken together, the marriage of statistics and mathematics in social network analysis has already produced some very useful ways of looking at patterns of social relations.
    • It is likely that this interface will be one of the areas of most rapid development in the field of social network methods in the coming years.