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When a computer network connects people or organizations, it is a social network.
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a social network is a set of people (or organizations or other social entities) connected by a set of social relationships, such as friendship, co-working or information exchange.
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This paper describes the use of the social network approach for understanding the interplay between computer networks, CMC, and social processes.
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Social network analysis focuses on patterns of relations among people, organizations, states
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seek to describe networks of relations as fully as possible, tease out the prominent patterns in such networks, trace the flow of information (and other resources) through them, and discover what effects these relations and networks have on people and organizations.
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eek to describe networks of relations as fully as possible, tease out the prominent patterns in such networks, trace the flow of information (and other resources) through them, and discover what effects these relations and networks have on people and organizations.
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examine how involvement in such social networks helps to explain the behavior and attitudes of network members -
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The social network approach facilitates the study of how information flows through direct and indirect network ties, how people acquire resources, and how coalitions and cleavages operate.
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a group is only one kind of social network, one that is tightly-bound and densely-knit.
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limiting descriptions to groups and hierarchies oversimplifies the complex social networks that computer networks support
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Much CMC research concentrates on how the technical attributes of different communication media might affect what can be conveyed via each medium.
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These characteristics include the richness of cues a medium conveys
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the visibility or anonymity of the participants
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and the timing of exchanges
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A reduction in cues has been cited as responsible for uninhibited exchanges (e.g., flaming), more egalitarian participation across gender and status, increased participation of peripheral workers, decreased status effects and lengthier decision processes
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Social network analysis reflects a shift from the individualism common in the social sciences towards a structural analysis
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suggests a redefinition of the fundamental units of analysis and the development of new analytic methods
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The unit is [now] the relation, e.g., kinship relations among persons, communication links among officers of an organization, friendship structure within a small group.
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Social network analysts look beyond the specific attributes of individuals to consider relations and exchanges among social actors.
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exchanges that create and sustain work and social relationships.
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Relations (sometimes called strands) are characterized by content, direction and strength. The content of a relation refers to the resource that is exchanged.
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A relation can be directed or undirected.
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Relations also differ in strength
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A tie connects a pair of actors by one or more relations
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Ties are often referred to as weak or strong,
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Pairs who maintain strong ties are more likely to share what resources they have
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The more relations (or strands) in a tie, the more multiplex (or multistranded) is the tie
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The composition of a relation or a tie is derived from the social attributes of both participants:
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A set of relations or ties reveals a social network.
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One approach considers the relations reported by a focal individual
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ego-centered (or "personal") networks provide an Ptolemaic views
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Copernican, approach considers a whole network based on some specific criterion of population boundaries such as a formal organization, department , club or kinship group. This approach considers both the occurrence and non-occurrence of relations among all members of a population.
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Ego-centered network analysis can show the range and breadth of connectivity for individuals and identify those who have access to diverse pools of information and resources. Whole network analysis can identify those members of the network who are less connected by CMC as well as those who emerge as central figures or who act as bridges between different groups
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Range: Social networks can vary in their range: i.e., in their size and heterogeneity.
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Larger social networks have more heterogeneity in the social characteristics of network members and more complexity in the structure of these networks [Wellman & Potter, 1997]. Small, homogeneous networks are characteristic of traditional work groups and village communities;
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may be important to examine who is central or isolated in networks maintained by different media
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Social network analysis has developed measures of centrality which can be used to identify network members who have the most connections to others (high degree) or those whose departure would cause the network to fall apart
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Similarities in network members' behavior suggest the presence of a network role
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Regularities in the patterns of relations (known as structural equivalence) across networks or across behaviors within a network allow the empirical identification of network roles.
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In social network analysis, a group is an empirically discovered structure
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groups emerge as highly interconnected sets of actors known as cliques and clusters.
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Social network analysts want to know who belongs to a group, as well as the types and patterns of relations that define and sustain such a group.
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Network density is one of the most widely used measures of social network structure: i.e., the number of actually-occurring relations or ties as a proportion of the number of theoretically-possible relations or ties.
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By contrast, few members of sparsely-knit networks communicate directly and frequently with each other
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The social network approach can also be used to see where relations and ties cross media lines.
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As well as partitioning social network members by groups, analysts also partition members by similarities in the set of relations they maintain.
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Those who share empirically-identified positions are likely to share similar access to informational resources.
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One social network method, blockmodeling, inductively uncovers such underlying role structures by juxtaposing multiple indicators of relationships in analytic matrices
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blockmodeling can partition social network members while simultaneously taking into account role relationships such as giving or receiving orders, socializing, collaborating, and giving or receiving information.
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The " web [network] of group affiliations" [Simmel, 1922] identifies the range of opportunities as well as the constraints within which people operate.
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People are usually members of a number of different social networks, each based on different types of relationships and, perhaps, different communication media
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Not only do people link groups, but groups link people; there is a "duality of persons and groups"
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Computer networks are only one method of maintaining ties, and social networks are not restricted to one medium
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"Computer-Assisted Social Networks" (CASNs) to acknowledge that social networks often use both computer and non-computerized media to sustain relations and ties.
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Ego-centered Networks: Social network analysts gather relational data at different levels of analysis, such as individuals, ties, clusters, or whole networks [Wasserman and Faust, 1994]. In an ego-centered network study, a set of people (selected on the basis of some sampling criteria) are asked questions in order to generate a list of people (alters) who are the members of their personal social network
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observing people's specified relations with a sample of their network members,
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Software logging may make it technically feasible for scholars to collect data about all those with whom a person is in contact online, although substantial coding and privacy-invasion questions remain for dealing with the content of these communications
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people are often given a roster of all the people in a specific group, and asked to identify a connection of some specific content
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researchers must consider where they are going to draw the boundaries or limitations of the sample. Since indirect as well as direct relations can become data, the boundary expands exponentially.
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Information about social networks is gathered by questionnaires, interviews, diaries, observations and more recently through computer monitoring.
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often asked to identify the frequency of communication with others as well as the medium of interaction
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Respondents are often asked to recall behavior that took place over a broad time frame in order to capture as much information as possible. If the time frame is too long, or the amount of information too detailed, reliability and accuracy are jeopardized.
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data based on recall, although widely used, may be less reliable than data gathered by observation
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Data gathered by self-reporting may be tapping into a different meaning of a communication episode than data gathered by observation. Thus, recall may be better for perceptions of media use, while observation or electronic data gathering may be better for measuring actual use.
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Most network researchers agree that the best approach is to use a combination of methods
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Gathering data electronically replaces issues of accuracy and reliability with issues of data management, interpretation, and privacy.
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can routinely collect information on whole networks or selected subsample
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The amount of information that can be gathered through automated means can be so overwhelming as to pose challenges for interpretation and analysis.
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it is difficult to assess the relative importance of electronic interactions captured in a log
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Since electronic data can be collected unobtrusively, it is more difficult for people to maintain control over what information is gathered and how it will be used in the future.
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Ego-centered data are often analysed using standard computer packages for statistical analysis
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If the aim is tie-level analysis, then all ties from all networks are analysed as if they were from one grand sample of ties.
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If the aim is network-level analysis, summary measures of each network's composition can be calculated using these packages
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Whole network studies examine the structure of social networks (including groups or blocks), as well as the networks' composition, functioning, and links to external environments.
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Networks can be described mathematically in a variety of ways
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Analyses of interaction frequency identifies the connections between people which can be used to build network models of resource flows or influence. They can also provide information on the overall density of interactions within a whole network or frequency of exchange among specific ties. Subgroups such as cliques are identified through partitioning the network into clusters of relative interaction density.
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Sociograms provide snapshots of organizational interaction structures which can indicate how static or dynamic these structures are over time.
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05 Sep 09
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adam muir(1997) When a computer network connects people or organizations, it is a social network. Yet the study of such computer-supported social networks has not received as much attention as studies of human-computer interaction, online person-to-person interact
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zpinheadWhen a computer network connects people or organizations, it is a social network. Yet the study of such computer-supported social networks has not received as much attention as studies of human-computer interaction, online person-to-person interaction, an
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04 Nov 07
Gary Ritzenthalerby Laura Garton, Caroline Haythornthwaite, and Barry Wellman
1998 journal research socialnetworks socialnetworking cmc theory web mmc3260
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16 Oct 07
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06 Sep 07
Angela RandallThis substantial article will demonstrate to you the importance of the conceptual frames that researchers use to guide the whole research process. It is also an interesting case study in research method, since it discusses how the data was collected
article collaboration education internet network reading socialnetworks thesis journal socialnetworking_essay social_networking netstudies_writingportfolio resources communication cmc sna social-networks jcmc online socialnetwork socialmedia web research
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27 May 07
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26 Sep 05
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