Social Network Theory (SNT) & Social Network Analysis (SNA)
Social Network Theory (SNT) and Social Network Analysis (SNA) <ul><li>Those that support the notion of a social network theory define it as a way of looking at individual relationships at a micro level, as well as at group/community relationships at a macro level. </li></ul><ul><li>Most studied attributes within social network theory: </li></ul><ul><ul><li>Content – nature of resource exchange </li></ul></ul><ul><ul><li>Direction – flow of resources </li></ul></ul><ul><ul><li>Tie Strength - strength of relationships </li></ul></ul><ul><li>In LIS context, social network analysis looks at patterns of information exchange – what kind of information is exchanged and between whom. </li></ul>These areas can be studied using social network analysis Information Needs Information Legitimation Information Opportunities Information Routes Information Exposure <ul><li>Social network analysis combines elements of mathematical graph theory and sociology to draw inferences about the characteristics of a human network. </li></ul>
Social Network Theory (SNT) and Social Network Analysis (SNA) <ul><li>Social network analysis provides tools for the information professional which can help in the identification, diagnosis, and modification of information routes. </li></ul><ul><li>By examining network structures, the information professional can identify flow and control in an environment, and can choose to fill gaps in the structure with services, advise clients on how to best use networks, or put in place the structures that will allow information to disseminate appropriately. </li></ul><ul><li>Social network analysis provides insight into the human network by the identification of cohesive social groups and key information brokers . Positions in a network reveal who controls, facilitates, or inhibits the flow of information, and who has similar information needs or uses. </li></ul><ul><li>A social network is comprised of nodes (also called actors) and ties (the relationship b/w two nodes). Information flows from one node to another via ties. </li></ul>
<ul><li>In 1967, psychologist Stanley Milgram randomly selected people living in Wichita, Kansas and Omaha, Nebraska and asked them to get a letter to a stockbroker in Boston whom they’d never met. His goal was to examine the average path length for social networks of people in the U.S. The subjects were given no information other than the man’s name and occupation and were only allowed to send the package to people they knew on a first name basis. In the end, the letters arrived in an average of six steps. </li></ul><ul><ul><li>This became known as the “Small World Experiment, ” and today is often referred to as the concept of “Six Degrees of Separation.” </li></ul></ul>Social Network Theory (SNT) and Social Network Analysis (SNA) http://www.digitaltonto.com/2009/forces-drive-social-networks/ Milestone studies
<ul><li>In 1996. Cornell graduate student Duncan Watts began researching how crickets seemed able to synchronize their chirping behavior, surmising that information about when to chirp was spreading through the cricket network. He began to explore how information flowed through human networks as well. </li></ul><ul><ul><li>Watts read Mark Granovetter’s “Strength of Weak Ties” theory, and also considered the ties he saw in the spacemen and cavemen characters he knew from science fiction -- the spacemen communicated remotely so that the people they knew didn’t know each other, while the cavemen lived in isolated groups and knew everybody their friends knew. Watts then built a mathematical model that would describe both situations and every possibility in between. </li></ul></ul>Social Network Theory (SNT) and Social Network Analysis (SNA) Milestone studies
<ul><li>Watts found as communities connect to each other, the social distance between people increases first, up to a point, but then decreases by an enormous amount. He concluded that globally connected networks with strong local cohesion are possible, with only a relatively small number of Granovetter’s “weak ties” mixed in to make it work. </li></ul><ul><li>Watts and his colleague Steve Strogatz went on to replicate Milgram’s “six degrees” study, using email communication, and verified his findings that a relatively small number of steps can connect everyone to each other. </li></ul><ul><ul><li>Today, Duncan Watts (right) directs the Human Social Dynamics Group at Yahoo! Research. </li></ul></ul>Social Network Theory (SNT) and Social Network Analysis (SNA) <ul><li>Social network theory offers these insights of relevance for today’s social media: </li></ul><ul><ul><li>Communities are primary , and a network is only as strong as the communities that it contains. </li></ul></ul><ul><ul><li>People want to connect </li></ul></ul><ul><ul><li>A small number of extremely active members drive network growth. </li></ul></ul><ul><ul><li>A network grows both outward and inward , with relatively slow growth until a “small world network” is formed, resulting in rapid, global growth. </li></ul></ul>Milestone studies
<ul><li>Haythornthwaite introduced five principles used to examine social networks </li></ul>Social Network Theory (SNT) and Social Network Analysis (SNA) <ul><li>Director of the School of Library, Archival and Information Studies at the University of British Columbia </li></ul><ul><li>One of the first scholars to apply social network analysis to the study of online communities and online learning. </li></ul>Caroline Haythornthwaite Cohesion Describes attributes of the whole network, indicating the presence of strong socializing relationships among network members, & likelihood of their having the access to same information resources. Structural Equivalence Identifies actors with similar roles. Actors are considered to be structurally equivalent if they fill the same role with respect to members of the same network. Prominence Measures of prominence indicate which actor(s) have influence or power in a network. Range The array of sources to which an actor has access. Brokerage relations Connections between disorganized others. These connections represent entrepreneurial opportunities for those who occupy them.
Social Network Theory (SNT) and Social Network Analysis (SNA) http://socialnetworkinglibrarian.com/2010/12/21/social-media-and-library-trends-for-2011/ Librarian AnnaLaura Brown, whose blog, Social Networking Librarian, provides resources for libraries interested in expanding their social networking practices, offers these predictions: Social media and library trends for 2011 1. Mobile applications, particularly those designed for library websites. 2. QR Codes, matrix barcodes 3. Google Applications, including Google Docs for collaboration and Google Voice for text messaging 4. Twitter, which can offer more than Facebook when it comes to reference and instant answers to questions 5. Increased use of Virtual Reference 6. Increased collaboration between librarians at more than one institution as well as between faculty and librarians 7. Increase in librarians teaching social media classes 8. Using social media as a teaching tool and not just as a tool for library promotion.