Corporate social networks - world usability day
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Presentation about corporate social networks and social network analysis at the world usability day
!["The Intranet tends to follow trends
from the web, and social networking is
no exception"
[Nielsen Norman Group 2009]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Corporate social networks - world usability day
- 1. corporate social networks Guillaume ERETEO – world usability day
- 2. "The Intranet tends to follow trends from the web, and social networking is no exception" [Nielsen Norman Group 2009]
- 3. "It's better to structure information according to how people use it, rather than what department owns it" [Jakob Nielsen 2009]
- 4. enterprise 2.0 "the use of emergent social software platforms within companies, or between companies and their partners or customers" [Mc Afee 2006]
- 5. "emergent social software platforms" "digital environments in which contributions and interactions" are: • "globally visible and persistent over time" • performed with social softwares that "enable people to rendezvous, connect or collaborate through computer-mediated communication and to form online communities" • emergent, freeform, with "patterns and structure inherent in people’s interactions". [Mc Afee 2009]
- 6. intranet of people via @amcafee Search Links follow me @ereteog Authoring "read write web" Tags Extension see also Signals
- 7. Social Networks A social network is made of actors (people, organizations, group) that are tied by social links.
- 8. • explicit and declared relations • interactions between actors • affiliation between actors Social links colleague communicate skill skill web
- 9. the bull's eye of @amcafee • Strong links: close collaborators • Weak links professional acquaintances • Potential links: professional proximity • Absent relationships: remainder of the network
- 10. Social capital "resources embedded in one's social networks, resources that can be accessed or mobilized through ties in the networks" [Lin 2008]
- 11. enterprise 2.0 and corporate social capital via @amcafee Wiki, online office suites: • collaboration • productivity • agility social networking service: • link maintenance • non-redundant information • network bridging blog, social tagging: • efficient search • link formation • collective intelligence
- 12. overwhelming flow of social data
- 13. users need help for preserving the benefits of enterprise 2.0 software in order to efficiently handle there social capital
- 14. Social network analysis helps understanding and exploiting the key features of social networks in order to manage their assets, their life cycle and predict their evolution.
- 15. Critical mass
- 16. community detection Influences the way information is shared [Coleman 1988] influences the way actors behave [Burt 2000] distribution of actors and activities
- 17. Centrality: strategic positions Degree centrality: Local attention beetweenness centrality: reveal broker "A place for good ideas" [Burt 1992] [Burt 2004] Closeness centrality: Capacity to communicate [Freeman 1979]
- 18. transitivity of relationships evaluating social opportunities Peter Jack Paul
- 19. Analyzing intranet of people sound great! but… what for?
- 20. maintain strong links • exploit the semantic of links to filter notifications • highlight influent actors and popular resources not yet mobilized
- 21. strengthen weak links highlight valuable weak links that provide access to relevant assets and opportunities
- 22. filter potential social capital and connect communities and people that should collaborate bridge social gaps
- 23. Open problem: using analysis metrics to leverage social intranet usability
Notas do Editor
- "Il semble que le terme « masse critique » vienne d'une observation du trafic routier en Chine, où sans feux de signalisation aux croisements, les cyclistes attendent d'être assez nombreux, de faire masse pour s'engager et traverser ensemble. " Le principe de masse critique dans un réseau social correspond à un niveau d'activité à partir duquel le réseau change d'état de manière permanente. Par exemple, à partir d'un certain nombre de personne et d'un volume d'activité minimale d'interaction, un groupe de personne devient une communauté d'intérêt.
- Community detection helps understanding the global structure of a network and the distribution of actors and activities. Moreover, the community structure influences the way information is shared and the way actors behave. Information spread quickly in a community and is shared by most of it members.
- The centrality highlights the most important actors of the network and three definitions have been proposed by Freeman. The degree centrality considers nodes with the higher degrees (number of adjacent edges). The closeness centrality is based on the average length of the paths linking a node to others and reveals the capacity of a node to be reached. The betweenness centrality focuses on the capacity of a node to be an intermediary between any two other nodes. A network is highly dependent on actors with high betweenness centrality due to their position as intermediaries and brokers in information flow.