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Social Networks of Performance
The document discusses the anatomy and examples of social networks, emphasizing the importance of understanding their structure through concepts like nodes and edges. It outlines metrics used to analyze these networks, such as density, centrality, and the role of brokers in improving group cohesion. The document further emphasizes the significance of social networks in various contexts, including business and teamwork, and encourages analysis for performance enhancement.
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Social Networks of Performance
- 1. social networks ofperformance April 12, 2016 David L. Passmore, Penn State Rose M. Baker, University of North Texas
- 2. social networks ofperformance •Some network anatomy Vocabulary of networks; structure of network diagrams and graphs •Examples of networks Physical, virtual, biological, and social •A simple social network Identifying a network of relationships in a small work team •Metrics for networks Numbers that summarize information in large networks Identification of networks among session participants •Networks you know Networks that you believe might account for performance
- 3. First, some networkanatomy Learn the names and moving parts
- 4. Networks are connectionsamong things.
- 5. Networks are connectionsamong things. The “things” are called the nodes of the network.
- 6. Networks are connectionsamong things. The “things” are called the nodes of the network. The “connections” are called the edges of the network.
- 7. Networks are connectionsamong things. This image is called a network diagram or a network graph.
- 8. Networks are connectionsamong things. This image is called a network diagram or a network graph. The diagram or graph uses lines to show the connections among things.
- 9. Examples of networks Theyare everywhere
- 10. Physical, as ina storm water management system that connects street drains to corrugated pipes that, eventually, aggregate storm water to treatment plants.
- 11. Virtual, as ina network of linked computers.
- 12. Biological, as ina nervous system composed of synapses that pass chemical or electrical signals among neurons.
- 13. Networks also canbe social.
- 14. A social networkis composed of individuals or organizations that are linked by such social factors as friendship, kinship, common interest, or financial exchange.
- 15. Nodes = individualsor organizations A social network is composed of individuals or organizations that are linked by such social factors as friendship, kinship, common interest, or financial exchange.
- 16. Nodes = individualsor organizations Edges = social factors that connect individuals or organizations A social network is composed of individuals or organizations that are linked by such social factors as friendship, kinship, common interest, or financial exchange.
- 17. As with anynetwork, the structure of links among nodes in a social network is represented by a network diagram or graph.
- 19.
- 20. A simple socialnetwork Watch closely…it is a little like Three–card Monte
- 21. Members of afive–person team are asked from which other team members they seek client–related information.
- 22. Members of afive–person team are asked from which other team members they seek client–related information. A “1” is recorded in this table if a person in the rows labeled in the left– most column seeks information from a person in a column labeled at the top of the table.
- 23. Members of afive–person team are asked from which other team members they seek client–related information. A “1” is recorded in this table if a person in the rows labeled in the left– most column seeks information from a person in a column labeled at the top of the table. For example, Bill seeks information from Pam.
- 24. Members of afive–person team are asked from which other team members they seek client–related information. A “0” is recorded if information is not sought.
- 25. Members of afive–person team are asked from which other team members they seek client–related information. A “0” is recorded if information is not sought. For example, Pam does not seek information from Carol.
- 26. Members of afive–person team are asked from which other team members they seek client–related information. In this case, seeking information from oneself is not a valid response, and, therefore, a “0” is recorded in the diagonal elements of this square table.
- 27. Members of afive–person team are asked from which other team members they seek client–related information. Some team members seek client–related information from each other. For example, Pam and Pat share information with each other.
- 29. “Business is acobweb of human relationships.” —H. Ross Perot
- 30. “Business is acobweb of human relationships.” —H. Ross Perot “Call it a clan, call it a network, call it a tribe, call it a family: Whatever you call it, whoever you are, you need one.” —Jane Howard, novelist
- 31. Metrics for networks Thegraphs become big and complex…you need some summary numbers. We will create metrics for social networks among participants on this session.
- 32. Connections of Facebookfriends of North Americans
- 33. So, summary metricsare required to make sense of complex networks
- 34. Density is expressedas a proportion of the number of actual links present in the group relative to the number of possible non–redundant links in the group (i.e., if everyone had a relationship with everyone else in the group). There are 17 links (lines between each set of two people) among 12 people. There are 66 possible unique links among people (i.e., (12 x 11) ÷ 2 ). Therefore, the density of the network represented is 0.26 (i.e., 17 ÷ 66).
- 35. Central people oftenhave more influence within their network. The most common measure of centrality is degree centrality, which is a simple tally of the number of people attached to each person. For instance, person A has a “degree centrality” of 2 because this person connects to two other people. Person B has a degree of 5.
- 36. Person B hasa high betweenness centrality because this person has the highest number of the shortest paths among people in this network diagram.
- 37. The person withthe highest closeness centrality score is the person who goes through the fewest number of ties to reach everyone else in the network. Person A exhibits the highest closeness centrality in the social network diagrammed.
- 38. For instance, personA is at a distance of 2 links from person B. This distance is calculated for all possible pairs of people in the network, and the average distance in the group indicates the group’s cohesion. A simple metric for cohesion is the density.
- 39. Some people areisolated from the group, such as the person represented by the isolated dot who is not connected to any other person in the network diagram. The single isolate identified represents 8% of the members of the network (i.e., 1 ÷ 12). Isolates are common in newly formed groups or in groups that are introducing new members. Network development seeks to integrate isolates into the web of relationships that help the group operate and communicate.
- 40. Within a clique,every person is connected to every other person. For example, the group of people with person B at the center forms a clique. Analysis of the membership of separate cliques reveals if they share overlapping members, who could provide paths for brokering relationships among cliques. A social network that contains highly segregated cliques is not as well integrated as a network in which people belong to several overlapping cliques.
- 41. A broker isin a position to manage information flow. A broker is in a privileged role and stands in a critical position for improving cohesion in the group. Person A is the single link between two distinct subgroups in the network portrayed. Therefore, person A is a potential broker between the two cliques.
- 42. Networks you know Wewill discuss possibilities that you see for network analysis to improve performance.