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Digital Living and Social Networks

Digital Living and Social Networks. Alessio Malizia, Prof., PhD , Computer Engineering Dep. University Carlos III of Madrid, Spain amalizia@inf.uc3m .es. dei.inf.uc3m.es dei@uc3m.es. Universidad Carlos III de Madrid. Madrid. Universidad Carlos III de Madrid. Informatics at UC3M.

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Digital Living and Social Networks

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  1. Digital Living and Social Networks Alessio Malizia, Prof., PhD, ComputerEngineering Dep. University Carlos III of Madrid, Spain amalizia@inf.uc3m.es dei.inf.uc3m.es dei@uc3m.es

  2. Universidad Carlos III de Madrid Madrid

  3. Universidad Carlos III de Madrid

  4. Informatics at UC3M • Thedegree in InformaticsEngineeringof Universidad Carlos III of Madrid has thefollowingprincipaldistinctivefeatures:  • 4-yeareducation, taking 240 credits. Internationalization, as itis a degreethatisadaptedtothe European HigherEducationArea (EHEA).  • PossibilityofchoosingEnglish/Spanishbilingualeducation. Newteachingmethodsadaptedtothe EHEA thatincludeongoingevaluation, groupwork, etc., toquantifyallthestudent’swork, notjustthat in theclassroom.  • Largepracticalcomponent, as at least 40% of total creditweightisdedicatedtotutoredlaboratorypracticum.  • Existenceofteachingresourcesadjustedtothenumberofstudents, withclassroomsandlaboratorieswhere a computerperstudentisavailable in many cases.  • Possibilityofcarrying out in-companyinternships. Possibilityofstudying in EuropethroughErasmusexchanges. There are currentlyagreementswith a numberofuniversities. • Outstandingdedicationoftheteachingfacultywho are highlyexperiencedand are in constantcontactwiththestudent. • AllthesefeatureshaveenabledInformaticsEngineering at Universidad Carlos III of Madrid toholdsecond place in the NATIONAL ranking ofdegreespublished in "El Mundo" newspaper in May 2008, andtheemployabilityofthesegraduatesis 100%, just as soon as theyfinishtheirstudiesand even before.

  5. DEI Lab @ UC3m • Web applications • Informationaccess • Interactive systems dei.inf.uc3m.es dei@uc3m.es

  6. Outline • Digital Living • Social Networks as • Science • Technology • Popular Culture • Developing for Cooperation • Tagging • Mash-ups • Conclusions

  7. Entertainment Communication & Collaboration Working and Learning Daily Life

  8. Evolution of Digital Living Digital Interaction living digital ecosystems environment for network People, community, Society Ergonomy Content Management Digital Rights Management Management of Change Crowdsourcing Knowledge sharing Web Services and Solutions e-business tools website Outsourcing Virtual Enterprises e-commerce tools e-mail Supply Chains Value-chain integration Reduction of distribution costs On-line market and payments Maximize accessibility to global markets Visibility and diffusion of information Internal/ External Communications Extent of economical impact, organizational change and sophistication*

  9. Focus switch Technology Computers Supercomputers Programming Optimization Applications and Services People Mobile Devices Usability, Universal Access

  10. DIGITAL INTERACTION

  11. Participant Designer Producer and Consumer Interconnected Perspective on Users User Customer Producer or Consumer Stand Alone

  12. UserParticipant

  13. Participant Designer Producer and Consumer Interconnected Perspective on Users User Customer Producer or Consumer Stand Alone

  14. AudienceDesigner

  15. Participant Designer Producer and Consumer Interconnected Perspective on Users User Customer Producer or Consumer Stand Alone

  16. ConsumerandProducer

  17. ConsumerandProducer

  18. Participant Designer Producer and Consumer Interconnected Perspective on Users User Customer Producer or Consumer Stand Alone

  19. Stand aloneInterconnected

  20. Outline • Digital Living • Social Networks as • Science • Technology • Popular Culture • Developing for Cooperation • Tagging • Mash-ups • Conclusions

  21. Social Networks

  22. social networks as science • Social network analysis is an interdisciplinary social science, but has been of special concern to sociologists. • Recently, physicists and mathematicians have made large contributions to understanding networks in general (as graphs) and thus contributed to an understanding of social networks too.

  23. social networks as science • [Social network analysis] is grounded in the observation that social actors [i.e., people] are interdependent and that the links [i.e., relationships] among them have important consequences for every individual [and for all of the individuals together]. ... [Relationships] provide individuals with opportunities and, at the same time, potential constraints on their behavior. ... Social network analysis involves theorizing, model building and empirical research focused on uncovering the patterning of links among actors. It is concerned also with uncovering the antecedents and consequences of recurrent patterns. (from Linton C. Freeman)

  24. social networks as science A • A and B are “structurally equivalent” because they connect to the same people and thus have equivalent positions in the network. B

  25. social networks as science Centrality is computed from the number of direct connections between nodes. Diane is central (6/9); Jane is not (1/9). orgnet.com/sna.html

  26. social networks as science • if you’re a boy in this network (a triangle) • and you want to meet a girl (a circle), • who are you going to call for an introduction? Bridge

  27. social networks as technology • email, newsgroups, and weblogs. • In the design of the arpanet (the forerunner to the internet) email was an afterthought!

  28. social networks as technology • search engines: e.g., Google (www.google.com) • Google’s Page Rank algorithm gives more weight to popular webpages. • A webpage is considered popular if many other webpages link to it. • collaborative filtering and/or recommender systems; e.g., amazon.com’s feature: “People who bought this book also bought...” • Amazon Mechanical Turk • Artificial Artificial Intelligence

  29. social networks as technology http://quartz.syr.edu/rdlankes/blog/?cat=5

  30. social networks as popular culture

  31. social networks as popular culture • e.g., six degrees of kevin bacon • bacon number: definition http://en.wikipedia.org/wiki/Six_Degrees_of_Kevin_Bacon • kevin bacon has a bacon number of 0 • an actor, A, has a bacon number of 1 if s/he appeared in a movie with kevin bacon • an actor, B, has a bacon number of 2 if s/he appear in a movie with A • etc. • Tryit at http://oracleofbacon.org/

  32. social networks as popular culture • Social software; e.g., facebook, friendster, orkut, tribe, etc. • Recall the article by danahboyd: what happens to social networks when they are explicitly declared? • “[danah] emphasize[s] how users have repurposed the technology to present their identity and connect in personally meaningful ways while the architect works to define and regulate acceptable models of use.” • To understand “artificial” social networks we need to rethink the social scientific concepts of “equivalence,” “centrality,” even “node” and “link.”

  33. Outline • Digital Living • Social Networks as • Science • Technology • Popular Culture • Developing for Cooperation • Tagging • Mash-ups • Conclusions

  34. Developing for Cooperation By Gerhard Fisher

  35. Collaborative Tagging and Folksonomies • “Collaborative tagging” is used to describe the process by which people create and share their metadata tags • “Folksonomies” refers to the actual output, or the tags themselves.

  36. Folksonomies • Folksonomies (known also as “social classifications”) are user created metadata. • They are a grassroots community classification of digital assets. • The term “folksonomy” was created by Thomas Vander Val and represents a merging of the terms “folk” and “taxonomy.” • One form of explicit user created metadata was popularized in the late 1990s with link-focused websites called weblogs

  37. Where are folksonomies found? • Folksonomies are found in social bookmarks managers such as Del.icio.us (http://del.icio.us/) and Furl (http://www.furl.net/), which allow users to: • Add bookmarks of sites they like to their personal collections of links • Organize and categorize these sites by adding their own terms, or tags • Share this collection with other people with the same interests. • The tags are used to collocate bookmarks: • (a) within a user’s collection; and • (b) across the entire system, e.g., the page http://del.icio.us/tag/blogging will show all bookmarks that are tagged with “blogging” by any user. • There are no clearly defined relations between and among the terms in the vocabulary, unlike formal taxonomies and classification schemes

  38. Popular folksonomy sites • Del.icio.us (http://del.icio.us) • Flickr (http://www.flickr.com) • Frassle (http://www.frassle.org) • Furl (http://www.furl.net) • Simpy (http://www.simpy.com) • Spurl (http://www.spurl.com) • Technorati (http://www.technorati.com)

  39. Web Mashups • Mashupis a Web pageorapplicationthat uses and combines data, presentationorfunctionalityfromtwoor more sourcestocreatenewservices.

  40. Web Tools forMashups

  41. Anexample (eStorys)

  42. Tools forMashups • Differenttoolstocreatemashups • Yahoo Pipes • Microsoft PopFly • Google Mashups (deprecatedfromJanuary 2009) • Marmite • Karma • IBM’sQEDWiki • JackBe • Dojo

  43. Conclusions • Digital Living isforpeoplenotforUsers • Ubiquitous • Tangible • Integration • Newmodelsfordesignandparticipation • Tools forend-usersdevelopment • Web 3.0 vs Web 2.0

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