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Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, memes spread, information circulation, friendship and acquaintance networks, business networks, knowledge networks, difficult working relationships, social networks, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through sociograms in which nodes are represented as points and ties are represented

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rdf:type	Thing Election music genre
rdfs:label	Social network analysis (en)
rdfs:comment	Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, memes spread, information circulation, friendship and acquaintance networks, business networks, knowledge networks, difficult working relationships, social networks, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through sociograms in which nodes are represented as points and ties are represented (en)
rdfs:seeAlso	Social network analysis (criminology)
sameAs	Social network analysis Social network analysis Social network analysis Social network analysis
dbp:wikiPageUsesTemplate	dbt:About dbt:Authority_control dbt:Cleanup dbt:Commons_category dbt:Div_col dbt:Div_col_end dbt:Reflist dbt:See_also dbt:Short_description dbt:Further_reading_cleanup dbt:Sociology dbt:Network_science dbt:Social_networking
Subject	Community building Cultural economics Self-organization Social information processing Social network analysis Social networks Social systems Surveillance Systems theory Value (ethics) Internet culture Methods in sociology
gold:hypernym	Process
prov:wasDerivedFrom	http://en.wikipedia.org/wiki/Social_network_analysis?oldid=1073265682&ns=0
Wikipage page ID	325726 (xsd:integer)
page length (characters) of wiki page	53925 (xsd:nonNegativeInteger)
Wikipage revision ID	1073265682 (xsd:integer)
has abstract	Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks, memes spread, information circulation, friendship and acquaintance networks, business networks, knowledge networks, difficult working relationships, social networks, collaboration graphs, kinship, disease transmission, and sexual relationships. These networks are often visualized through sociograms in which nodes are represented as points and ties are represented as lines. These visualizations provide a means of qualitatively assessing networks by varying the visual representation of their nodes and edges to reflect attributes of interest. Social network analysis has emerged as a key technique in modern sociology. It has also gained significant popularity in the following - anthropology, biology, demography, communication studies, economics, geography, history, information science, organizational studies, political science, public health, social psychology, development studies, sociolinguistics, and computer science and is now commonly available as a consumer tool (see the list of SNA software). The advantages of SNA are twofold. Firstly, it can process a large amount of relational data and describe the overall relational network structure. tem and parameter selection to confirm the influential nodes in the network, such as in-degree and out-degree centrality. SNA context and choose which parameters to define the “center” according to the characteristics of the network. Through analyzing nodes, clusters and relations, the communication structure and position of individuals can be clearly described. (en)
foaf:isPrimaryTopicOf	http://en.wikipedia.org/wiki/Social_network_analysis
is Wikipage redirect of	Analysis of social networks Cascade (Social Network Theory) History of social network analysis Social Network Analysis Social Network Change Detection Social Networking Potential Social networking potential Social network change detection Networks in Political Science
is Link from a Wikipage to another Wikipage of	Forensic identification List of statistics articles Local World Evolving Network Models Loet Leydesdorff Marisa von Bülow Mark Mizruchi Marketing research NDTV Numbers (season 2) Numbers (season 3) Numbers (season 4) Numbers (season 5) 1997 Asian financial crisis Adolescent cliques Agent-based model Albert Bergesen Aleš Žiberna Alpha centrality Analysis Analysis of social networks Andrew McCallum Animal culture Ann Swidler Antonio Casilli Anuška Ferligoj Audience theory AusStage BROG Balance theory Barry Wellman Betweenness centrality Biased random walk on a graph Biological network Bipartite graph Montreal Economic Institute Main path analysis Camponotus fellah Cascade (Social Network Theory) Centrality Generalized blockmodeling of binary networks Global governance James G. Webster James H. Fowler Joseph Galaskiewicz Julia Hillner KXEN Inc. David Charles Benton David Krackhardt David R. Gibson

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