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Explore the concept of social networks and their impact on individual and collective behavior, with a focus on personal networks. Learn about essential network analysis concepts and techniques.
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SNA: An Introduction José Luis Molina joseluis.molina@uab.cathttp://pagines.uab.cat/joseluismolinawww.egolab.cat Màster en Direcció d'Empreses / Master in Management
What do we mean by“social networks”? • Social Media (twitter, Facebook, Whatsapp…) • Market oriented: Social Networking Sites • Adopted by Mass-Media. • Convergenge of social and tecnological networks (Kleinberg 2008) … • A metaphor about complexity • Castells, The Network Society(1999). • (…) • Emergent social structures • Communities, social circles, quasi-groups (Boissevain 1968) … • Transnational fields – diffusion of ideas, habits … • Informal organizational chart. • Industrial districts!
Theoretical questions … • Identification of the effect of emerging social structures in individual or collective behavior (rumors, Epstein 1969; strike, Kapferer 1972; political mobilization, Srinivas & Béteille 1964 ...). • Divergence between cognitive data and behavioral data. • Relations between micro and macro social structures. Contagion - Influence, strong / weak ties. RDS ... • Intracultural variation of local ecological knowledge. • Synchronicity of human activity (cities, regions, world). • Other ... (Adler-Lomnitz, Dunbar ...).
Basic definitions: centrality, cohesion, positions and structures
Whole networks– egonetworks, egocentric networks /personal networks • A whole/complete network is a collection of nodes and ties taken from a specific field of interaction (a classroom, a organization, an internet community…).
Boundary specification (Laumann et al. 1983) • Nominalistic • Imposed by the researcher’s analytical interests (“the network of interlocking directorates in Spain”). • Realistc • Boundaries reported by the participants (“people in this neighboorhod”). • Representative sampling is not possible (or by sampling 80%). • Important/influential people can be easily identifed (indegree / nominations).
Ego-centric analysis: ego networks • A “egonetwork” is the neigborhood of a given ego within a whole network. • Every ego is a node of the whole network. • The analysis focuses on the egonetwork level, including ego.
Ego-centric networks /personal networks • A“personal network” is the set of people and ties of a given individual in different fields of interaction, along with the alter-alter ties. • Ego is typically not represented. • The analysis is conducted at the individual level. • Representative sampling is applicable.
Combination… • Personal networks can be combined into a whole network.
Network data... • Namegenerators (cognitive data): questionsthatprovidenames of people in return. • Eachnamegenerator can generate a differentnetwork. • Digital activitylogs (time, location, from, to, content … behavioral data) . • Usuallymanyobservations and few ítems byeach case (phonecalls, Facebook likes, etc.) • Others (letters, officialregisters, etc.)
Types of name generators… • Onenamegenerator vs. multiplenamegenerator • Free list vs. fixedlist. • Free size / fixednumber of nominations.
Network ties can be… • Bynary (1, 0) or valued (e.g. 0-5). • Oriented or reciprocal
“Name interpreters” / attributes • The list of descriptives of each alter nominated: • Sociodemographics • Ego-alter closeness. • Geographic location. • …
Types of matrices • One-mode= same set of actors/nodes/vertices on rows and columns. • Two-mode= one set of actors on rows and a different set of actors or events on columns. Also called Affiliation Matrices. • It is possible to convert two-mode matrices to one-mode (rows * rows or columns * columns).
... Matrix one-mode... 1 1 1 1 1 1 2 3 4 5 6 7 8 9 0 1 2 3 4 AMRVGBEGJSJMMOCRPPGGJLMAFGDE - - - - - - - - - - - - - - 1 AMG 0 0 0 0 0 0 1 1 0 0 1 0 0 0 2 RVT 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 GBB 0 0 0 0 0 1 0 0 0 1 1 0 0 0 4 EG 0 0 0 0 0 0 0 0 0 0 1 0 0 0 5 JSP 0 0 0 0 0 0 1 1 0 0 1 0 0 0 6 JMF 0 0 1 0 0 0 1 0 0 1 1 0 0 0 7 MOS 1 0 0 0 1 1 0 1 0 0 1 0 0 0 8 CR 1 0 0 0 1 0 1 0 0 0 1 0 0 0 9 PP 0 0 0 0 0 0 0 0 0 0 1 1 0 0 10 GG 0 0 1 0 0 1 0 0 0 0 1 0 0 0 11 JLM 1 1 1 1 1 1 1 1 1 1 0 0 0 0 12 MAR 0 0 0 0 0 0 0 0 1 0 0 0 1 0 13 FG 0 0 0 0 0 0 0 0 0 0 0 1 0 0 14 DES 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Some basic concepts from graph theory … • Path • Geodesic • Component • Diameter • …
Network level: density or av. degree, component, centre-perifery
Group-level • Group detection following the cohesion strategy. • Newman-Girvan • Tab “Analysis”: grouping, clustering, modulartiu, girvan-Newman apply • This operation creates a new attribute that can be seen in the Attribute Manager and gives a value to each group. This value can be used to differentiate / color / merge the different groups.
Collection of network data… • Link List … • Ego, alter, value: • Tom Cruise, Nikole Kidman, 5 • Tom Cruise, Penélope Cruz, 3 • Nikole Kidman, Tom Cruise, 2 • Nikole Kidman, Penélope Cruz, -5 o • Nikole Kidman, Penélope Cruz, 0 • (in case of absence, the dyad means a value of “1”). • Attributes … • Artist, sex, age, nationality, or degree of innovation, market share…
Import Link List + Atributes to visone • visone.info • Webstartordownload • Ejecutar el programa • Descargar fichero CSV con los enlaces (en el escritorio). • Descargar fichero CSV con los atributos (en el escritorio) • Importar (file > open) en primer lugar el fichero links.
Análisis a nivel de red • Medidas de cohesión (densidad, reciprocidad, transitividad …). • Componentes • Estructura centro-periferia • (…) • Tab Analysis: task: indexing; class: network; index: network statistics, seleccionar densidad, average degree, conn. components, # nodes in max core. • Apply • Attribute Manager> Show/edit.
Some links... • INSNA http://www.insna.org/ • Web Redes http://www.redes-sociales.net • Revista REDES http://revistes.uab.cat/redes
