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    Based on an organizational perspective, the software permits an analyst to register or import all of the actors into the system, join them into teams or groups, and assign them roles.

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    The team states that the personal network feedback enables by itself each actor to assess his connectivity within the network and improve it by planning changes.

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    Subsets or subgroups can be identified and studied separately in the network.

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    These kinds of nodes are called cutpoints.

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    Social Network Analysis can be in different contexts and how social networks can be represented, extracted, and analyzed in information systems.

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    Matrices contain the same information as graphs but are more suitable for calculation in the analysis.

    SNA is a powerful managerial tool because it makes visible the patterns of relationships within and across strategically important networks (Cross and Parker 2004).

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    Although the software itself has standard procedures to analyze and visualize networks, it can also export data to most common formats.

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    Most of the content and.

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    This analysis facilitates the addition of social networks as well as their automatic extraction from existing information repositories.

    Looking to the sociogram, we can understand that actors in lower hierarchical positions can have great importance inside the organization due to their knowledge, role, or personal relationships with other peers.

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    One reason for the use of mathematical and graphical techniques in SNA is their ability to represent the descriptions of networks compactly and systematically (Jamali and Abolhassani 2006).

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    Social Networking Services, opened new opportunities to explore the power of social networks inside and outside organizations.

    Finally, we present SNARE (Social Networking Analysis and Reengineering Environment), a system we are currently developing that proposes to integrate Organization Network Analysis and Social Networking Services with different approaches and techniques.

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    As Rob Cross states in his book, real organizations are typically different from those expressed in organizational charts (Cross and Parker 2004).

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    The most notable influence was Jacob Moreno, who investigated how an individual's group relationships affected his own actions and development.

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    Nodes are the individual actors within the networks, and ties are the relationships between the actors.

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    Unlike Ucinet, Pajek has no direct procedures for detecting cliques due to the difficulty of this procedure for large networks.

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    Actors occupy the first line and first column of a matrix composed of as many rows and columns.

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    After that, the analyst can create a survey with questions to infer all of the social relationships in the network as well as their strength or frequency.

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    Advanced visualization techniques are present in Pajek: network drawing.

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    As depictured in Figure 2, this section surveys approaches and formats for representing Social Networks as well as approaches, tools, and services supporting Social Network Analysis.

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    This chapter surveys the basic concepts of social networks methods, approaches, tools, and services.

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    Management consultants use this methodology with business clients and refer to it as Organizational Network Analysis (ONA).

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    The same reasons, when introduced into department and project separation, can produce a lack of communication, lack of awareness of resources, and lack of collaboration between actors within a company.

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    Netminer is a commercial product developed by Cyram and contains analysis and visualization techniques (Cyram 2007).

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    Directly linked with this concept are the members who would disconnect the group if they were removed.

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    Sna measures To perform SNA, it is necessary to define measures that can be compared between actors or networks.

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    The packages can range from complete software to analyze and visualize social networks to systems that permit the design and execution of surveys and then use the data obtained to perform a full network analysis.

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    It thus offers a powerful tool for uncovering patterns in the network (Cross and Parker 2004).

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    The analyst can view and analyze the results of the complete network.

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    Other important concepts are the geodesic distance (the shortest distance between one node and another in the graph) and the structural equivalence (the extent to which an actor shares the same set of links with another).

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    After closing the survey, an individual action plan is available to all actors with the analysis of their own answers.

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    The relationships between actors can be also classified based on cardinality: a dyad is a linkage or relationship between two actors and a triad involves a triple of actors and associated ties.

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    Measures in SNA can be distinguished as those that evaluate the entire network and those that evaluate only a specific node (Wasserman and Faust 1994).

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    Other systems allow the automatic discovery of network information via mining a data repository or communications gateway.

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    It contains a large number of network analysis methods, such as analysis procedures for computing centrality degree, ego network analysis, and the detection of subgroups and structural holes in both the entire and parts of the network.

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    The introduction of computational methods opened new opportunities for the use of social networks by allowing the analysis of larger datasets.

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    After that, different software tools for performing SNA are analyzed.

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    Graph theory provides a vocabulary that can be used to label social structural properties: points called nodes are used to represent actors, and lines or arrows connecting the points are used to represent links.

    SNA is now used wherever a social network is present, and its study can be interesting for understanding and improving any group process.

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    Social Networks in Information Systems.

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    Cohesion measures the percentage of actors directly connected to each other by cohesive ties.

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    Social Network Analysis (SNA) has been used as a powerful tool in organizations to understand the connections and influences both inside and outside the organization as well as how these connections affect the performance of core processes.

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    Social Network Analysis studies the patterns of relationships among social entities and can be used to understand and improve group processes.

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    Centralization is directly connected with the notion of central nodes: a more centralized network indicates that most of the ties are dispersed around one or a few nodes.

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    Other kinds of tools, including initial surveys to infer relationships in a network, have appeared to aid SNA.

    At the network level, it is important to understand how the network is structured.

    Path Length is defined as the average of the distance between all pairs of nodes.

    The software permits the registration of actors present in the network, and then it allows users to define a survey and use the data received from the answers to perform a social network analysis.

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    Moreno was credited of devising a sociogram as a way to depict such social relationships (Fredericks and Durland 2005).

    Social networks tools The common way to extract a social network is by instantiating it directly through SNA software packages.

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    Main scope of Social Network Software.

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    Reingold (Fruchterman and Reingold 1991) are good examples of this kind of technique.

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    Several software packages that support Social Networks Communities or perform SNA are available.

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    This measure evaluates an actor's position in the network and can be interpreted as the prominence of an actor in the social group.

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    Some statistical procedures are also available, and Pajek can invoke directly statistical software.

    Structural Hole is linking to ideas of social capital, for example, if you link two people who are not linked, you can control their communication.

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    Both social actors and links may have additional attributes that express additional information about them.

    Most of the software packages analyzed share common features to extract, analyze, and visualize social networks.

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