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Thursday 23rd February 2012
                              JISC CETIS Conference 2012


                                 Author: Amber Thomas
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Social Network Analytics
Amber Thomas
JISC Programme Manager
http://slidesha.re/z44AqU
Thursday 23rd February 2012
                     JISC CETIS Conference 2012




     Social Networks
in Education and Research


 Social Network Analytics
in Education and Research


       Examples
Who are the social networks in education?



Who is the social network?
• inside the institution:
   o academics: as researchers
   o academics: as teachers
   o services:
     libraries, IT, catering, accommodation, conferences
   o students
• institutional management has different levels of control, each
  has different motivations
• outside the institution:
   o potential learners and informal learners
   o the public/society
   o journalists
   o employers

Not everyone engages in the same way:
Users and non users, visitors and residents                        3
A first look:
                                    Social network use in education

                                      wikis as collaboration
                                      student as media producer
A message and a medium
                                      practitioner peer to peer
                                      amplification of teaching
  Social media as speaking
  (marketing)                         amplification of events
  Social media as listening (user     broadcasting platforms e.g youtube
  feedback, market intelligence)
                                      blogging as digital scholarship
  Social media as exchange
  (learning, scholarship, CRM?)       blogging as services update
                                      universities on facebook
                                      twitter as alerts
                                      twitter as exchange

                                                                           4
The value of social networks in education


Lets give social networks the benefit of the doubt:
They are a good thing
They are a useful thing
Lets assume no-one is questioning that.


So ... social networks generate data. Can that data help to:
 Show the value of social networks?
 Enhance the value of social networks?
 Improve the way we use social networks?


What’s not to like?
                                                               5
Is social network analysis a trap?




                                6
Thursday 23rd February 2012
                     JISC CETIS Conference 2012




     Social Networks
in Education and Research


 Social Network Analytics
in Education and Research


       Examples
Who’s agenda is this anyway?



      comfort zone                     dirty words


OPEN ACCESS TO RESEARCH                  IMPACT
    OPEN INNOVATION                      BRAND
  OPEN EDU RESOURCES              COST BENEFIT ANALYSIS
  KNOWLEDGE SHARING                     METRICS
  ACADEMIC AUTONOMY                       KPIs
      PUBLIC GOOD                    BUSINESS CASES


  LANGUAGE OF VALUES             LANGUAGE OF THE MARKET

                                                          8
[Data capture is not [Analytics] is not Metrics]




   DATA CAPTURE

The Data Exists Anyway




                                         METRICS
                                        (come later)

                                                       9
Demystifying the role of data in decision-making




                                            DECISIONS

  “Evidence-based decision making”
                  &
    “Data-driven decision making”



                                     DECISION-
METRICS           EVIDENCE           MAKER(s)




                                                        10
Demystifying the role of data in decision-making
                                           the messy reality


“Evidence-informed           RESOURCES
  & data-informed                                  DECISIONS
  decision making”
                           VALUES



                     STRATEGIES


                                            DECISION-
                       EVIDENCE             MAKER(s)
    METRICS
                                    ETC !
           IMPACT
           MODELS    STAKEHOLDER
                        VIEWS

                                                               11
Demystifying data in an age of data




                             Opportunity:




                                                      LANGUAGE OF THE MARKET
                     Using the techniques of the
LANGUAGE OF VALUES




                     market to support our values
                         in the age of data

                                APIs
                               Feeds
                           Web analytics
                          Data visualisation
                             Storytelling


                                                                               12
Tactics for responding to the age of data



• deny it's happening
• leave the people in suits to
  work it out
• pay lip service
• produce numbers
• produce stories
• deepen our listening
  approaches
• improve our metrics
• broaden our impact model
• extend our impact timeframe


                                                        13
Thursday 23rd February 2012
                     JISC CETIS Conference 2012




     Social Networks
in Education and Research


 Social Network Analytics
in Education and Research


       Examples
The age of data



In the age of data, data is everywhere
   ... even if its not the whole story


   Decision-makers want numbers
... even if they don’t “understand” them


                  and
         People like pictures
Decision makers want numbers
  (even if they don’t understand them)

http://scaleofuniverse.com/
People Like Pictures
Principles for responding to the age of data



      In the age of data, data is everywhere
         Decision-makers want numbers
               People like pictures


                      BUT
        Not everything can be measured
       Not everything should be measured
        There are legal and ethical issues
Data can be mistaken, misunderstood and misused
A Lesson in Glorious Obfuscation




http://www.tubechop.com/watch/281562
Tactics for responding to the age of data




Reduce our fear of numbers
Be generous with data, not guarded
Increase our data literacy and our technical skills
Combine data, combine effort, work faster
Imagine we’re all talking to strangers
Every data it’s story, every story it’s data
Glanceability in an abundance of data: visual matters




                                                         20
Looking again:
                                    Social network use in education

                                      wikis as collaboration
                                      student as media producer
A message and a medium
                                      practitioner peer to peer
                                      amplification of teaching
  Social media as speaking
  (marketing)                         amplification of events
  Social media as listening (user     broadcasting platforms e.g youtube
  feedback, market intelligence)
                                      blogging as digital scholarship
  Social media as exchange
  (learning, scholarship, CRM?)       blogging as services update
                                      universities on facebook
                                      twitter as alerts
                                      twitter as exchange

                                                                        21
Examples



Aside from the Hirst and the Hawksey, please see also:
 Institutional use of social media eg Brian Kelly
   http://ukwebfocus.wordpress.com/
 New models of impact for research eg ALT Metrics
   http://altmetrics.org/manifesto/
 Learning analytics eg Siemens et al
   http://en.wikipedia.org/wiki/Learning_analytics
 Text mining twitter eg Proctor, Manchester
   http://www.guardian.co.uk/uk/2011/dec/07/twitter-riots-how-
   news-spread
My SNA Examples
                       Who is the hashtag community?


Heart of #UKOER

http://zoom.it/6ucv5

        By

 Martin Hawksey
UKOER Viz Project
My SNA Examples
         Are two people being listened to by the same people?




dkernohan & ambrouk

   Twiangulate
  Mutual Followers
     Analysis

       From
www.twiangulate.com




                      Following 205 people in common of 1050 total
                                    tweeps followed
My SNA Examples
                    Are two people listening to the same people?




dkernohan & ambrouk

    Twiangulate
   Mutual Friends
     Analysis

       From
www.twiangulate.com




                       Followed by 244 people in common of 1336
                                 total following tweeps
My SNA Examples
                                     A Rather Cunning and Brave
                                and Possibly Foolish Experiment:

How much use/reach/impact does this presentation have?
http://slidesha.re/z44AqU
See topsy tracking links in the notes of this presentation


Pick your favourite:
personal impact = pimpact
vanity analytics = vanalytics
Tweet/use your favourite term online
And I’ll do something interesting/useful/vain with it
Thank You

Amber Thomas
Programme Manager
Digital Infrastructure Team


Twitter: @ambrouk
Skype: amber_thomas


Full Contact Details:
http://www.jisc.ac.uk/contactus/staff/amberthomas.aspx
My blog posts: http://bit.ly/zBQ2er

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Social Network Analytics in Education and Research: Lies, Damned Lies and Pretty Pictures

  • 1. Thursday 23rd February 2012 JISC CETIS Conference 2012 Author: Amber Thomas (c) HEFCE on behalf of JISC www.jisc.ac.uk CC BY except slide templates, a logos and images unless otherwis stated Social Network Analytics Amber Thomas JISC Programme Manager http://slidesha.re/z44AqU
  • 2. Thursday 23rd February 2012 JISC CETIS Conference 2012 Social Networks in Education and Research Social Network Analytics in Education and Research Examples
  • 3. Who are the social networks in education? Who is the social network? • inside the institution: o academics: as researchers o academics: as teachers o services: libraries, IT, catering, accommodation, conferences o students • institutional management has different levels of control, each has different motivations • outside the institution: o potential learners and informal learners o the public/society o journalists o employers Not everyone engages in the same way: Users and non users, visitors and residents 3
  • 4. A first look: Social network use in education wikis as collaboration student as media producer A message and a medium practitioner peer to peer amplification of teaching Social media as speaking (marketing) amplification of events Social media as listening (user broadcasting platforms e.g youtube feedback, market intelligence) blogging as digital scholarship Social media as exchange (learning, scholarship, CRM?) blogging as services update universities on facebook twitter as alerts twitter as exchange 4
  • 5. The value of social networks in education Lets give social networks the benefit of the doubt: They are a good thing They are a useful thing Lets assume no-one is questioning that. So ... social networks generate data. Can that data help to:  Show the value of social networks?  Enhance the value of social networks?  Improve the way we use social networks? What’s not to like? 5
  • 6. Is social network analysis a trap? 6
  • 7. Thursday 23rd February 2012 JISC CETIS Conference 2012 Social Networks in Education and Research Social Network Analytics in Education and Research Examples
  • 8. Who’s agenda is this anyway? comfort zone dirty words OPEN ACCESS TO RESEARCH IMPACT OPEN INNOVATION BRAND OPEN EDU RESOURCES COST BENEFIT ANALYSIS KNOWLEDGE SHARING METRICS ACADEMIC AUTONOMY KPIs PUBLIC GOOD BUSINESS CASES LANGUAGE OF VALUES LANGUAGE OF THE MARKET 8
  • 9. [Data capture is not [Analytics] is not Metrics] DATA CAPTURE The Data Exists Anyway METRICS (come later) 9
  • 10. Demystifying the role of data in decision-making DECISIONS “Evidence-based decision making” & “Data-driven decision making” DECISION- METRICS EVIDENCE MAKER(s) 10
  • 11. Demystifying the role of data in decision-making the messy reality “Evidence-informed RESOURCES & data-informed DECISIONS decision making” VALUES STRATEGIES DECISION- EVIDENCE MAKER(s) METRICS ETC ! IMPACT MODELS STAKEHOLDER VIEWS 11
  • 12. Demystifying data in an age of data Opportunity: LANGUAGE OF THE MARKET Using the techniques of the LANGUAGE OF VALUES market to support our values in the age of data APIs Feeds Web analytics Data visualisation Storytelling 12
  • 13. Tactics for responding to the age of data • deny it's happening • leave the people in suits to work it out • pay lip service • produce numbers • produce stories • deepen our listening approaches • improve our metrics • broaden our impact model • extend our impact timeframe 13
  • 14. Thursday 23rd February 2012 JISC CETIS Conference 2012 Social Networks in Education and Research Social Network Analytics in Education and Research Examples
  • 15. The age of data In the age of data, data is everywhere ... even if its not the whole story Decision-makers want numbers ... even if they don’t “understand” them and People like pictures
  • 16. Decision makers want numbers (even if they don’t understand them) http://scaleofuniverse.com/
  • 18. Principles for responding to the age of data In the age of data, data is everywhere Decision-makers want numbers People like pictures BUT Not everything can be measured Not everything should be measured There are legal and ethical issues Data can be mistaken, misunderstood and misused
  • 19. A Lesson in Glorious Obfuscation http://www.tubechop.com/watch/281562
  • 20. Tactics for responding to the age of data Reduce our fear of numbers Be generous with data, not guarded Increase our data literacy and our technical skills Combine data, combine effort, work faster Imagine we’re all talking to strangers Every data it’s story, every story it’s data Glanceability in an abundance of data: visual matters 20
  • 21. Looking again: Social network use in education wikis as collaboration student as media producer A message and a medium practitioner peer to peer amplification of teaching Social media as speaking (marketing) amplification of events Social media as listening (user broadcasting platforms e.g youtube feedback, market intelligence) blogging as digital scholarship Social media as exchange (learning, scholarship, CRM?) blogging as services update universities on facebook twitter as alerts twitter as exchange 21
  • 22. Examples Aside from the Hirst and the Hawksey, please see also:  Institutional use of social media eg Brian Kelly http://ukwebfocus.wordpress.com/  New models of impact for research eg ALT Metrics http://altmetrics.org/manifesto/  Learning analytics eg Siemens et al http://en.wikipedia.org/wiki/Learning_analytics  Text mining twitter eg Proctor, Manchester http://www.guardian.co.uk/uk/2011/dec/07/twitter-riots-how- news-spread
  • 23. My SNA Examples Who is the hashtag community? Heart of #UKOER http://zoom.it/6ucv5 By Martin Hawksey UKOER Viz Project
  • 24. My SNA Examples Are two people being listened to by the same people? dkernohan & ambrouk Twiangulate Mutual Followers Analysis From www.twiangulate.com Following 205 people in common of 1050 total tweeps followed
  • 25. My SNA Examples Are two people listening to the same people? dkernohan & ambrouk Twiangulate Mutual Friends Analysis From www.twiangulate.com Followed by 244 people in common of 1336 total following tweeps
  • 26. My SNA Examples A Rather Cunning and Brave and Possibly Foolish Experiment: How much use/reach/impact does this presentation have? http://slidesha.re/z44AqU See topsy tracking links in the notes of this presentation Pick your favourite: personal impact = pimpact vanity analytics = vanalytics Tweet/use your favourite term online And I’ll do something interesting/useful/vain with it
  • 27. Thank You Amber Thomas Programme Manager Digital Infrastructure Team Twitter: @ambrouk Skype: amber_thomas Full Contact Details: http://www.jisc.ac.uk/contactus/staff/amberthomas.aspx My blog posts: http://bit.ly/zBQ2er

Editor's Notes

  1. This presentation: http://slidesha.re/z44AqUmade live on 2012/02/20 on the JISC slideshare channelfor a session at the on 2012/02/23 at the JISC CETIS Conference 2012 http://wiki.cetis.ac.uk/Conference_2012_Programme Author: Amber Thomas (c) HEFCE on behalf of JISC www.jisc.ac.ukCC BY except slide templates, all logos and images unless otherwise stated
  2. Let’s explore the resistance
  3. I think it is more like this
  4. So where do we start?
  5. http://scaleofuniverse.comData is everywhere, data is cheapThis is the era of zooming outYou are but a grain of sandThere are patterns in numbersThey are not the whole storyBut they are part of the storyAnyway, do you have the right to deny access to your stats?Do your stats belong to you? You didn’t make them, your users did.Do your stats belong to the social network?Does the social network need the stats to sustain itself in providing the service?FacebookTwitterLinkedInSlideshareCulture24BBCGovUKThe argument for open learning analytics: they belong to the network level
  6. http://www.flickr.comhttp://news.bbc.co.uk/1/hi/uk_politics/election_2010/8574653.stmhttp://www.informationisbeautiful.net/http://www.pinterest.comhttp://www.coolinfographics.com/ http://infonewt.com/ http://dev8d.org/ (emoticons: 8D = happy geek)
  7. Financial KidneysClip from The Day Todayhttp://www.tubechop.com/watch/281562(17 seconds)
  8. Use of the #ukoerhashtag from the JISC/HEA Programmehttp://www.jisc.ac.uk/oer Heart of #UKOERhttp://zoom.it/6ucv5ByMartin Hawksey UKOER Viz Project
  9. Spotted in the UKOER cloud:Two Programme Managers in slightly different spacesdkernohan & ambroukTwiangulateMutual FollowersAnalysisFrom www.twiangulate.com
  10. Two Programme Managers: different perspectivesdkernohan & ambroukTwiangulateMutual FriendsAnalysisFrom www.twiangulate.com
  11. This presentation:Full: http://www.slideshare.net/JISC/social-network-analytics-in-education-and-research-lies-damned-lies-and-pretty-picturesBitly: http://slidesha.re/z44AqUmade live 23:00 on 2012/02/20 on the JISC slideshare channelfor a session at the on 2012/02/23 at the JISC CETIS Conference 2012 http://wiki.cetis.ac.uk/Conference_2012_Programme The presentation of this url on topsyhttp://topsy.com/www.slideshare.net/jisc/social-network-analytics-in-education-and-research-lies-damned-lies-and-pretty-picturespersonal impact = pimpacthttp://www.google.co.uk/search?q=pimpacthttps://twitter.com/#!/search/realtime/%23pimpactvanity analytics = vanalyticshttp://www.google.co.uk/search?q=vanalyticshttps://twitter.com/#!/search/realtime/%23vanalytics
  12. Full Contact Details:http://www.jisc.ac.uk/contactus/staff/amberthomas.aspxMy blog posts: http://bit.ly/zBQ2erThank you!