Post on 26-Jan-2015
description
Social Network Analytics
Amber ThomasJISC Programme Manager
Thursday 23rd February 2012
JISC CETIS Conference 2012
http://slidesha.re/z44AqU
Author: Amber Thomas (c) HEFCE on behalf of JISC
www.jisc.ac.uk
CC BY except slide templates, all logos and images unless otherwise
stated
Thursday 23rd February 2012
JISC CETIS Conference 2012
Social Networksin 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 researcherso academics: as teacherso services: libraries, IT, catering, accommodation,
conferenceso students
• institutional management has different levels of control, each has different motivations
• outside the institution:o potential learners and informal learnerso the public/societyo journalistso employers
Not everyone engages in the same way:Users and non users, visitors and residents
3
A first look:Social network use in education
A message and a medium
Social media as speaking (marketing)
Social media as listening (user feedback, market intelligence)
Social media as exchange (learning, scholarship, CRM?)
wikis as collaboration
student as media producer
practitioner peer to peer
amplification of teaching
amplification of events
broadcasting platforms e.g youtube
blogging as digital scholarship
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?
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Is social network analysis a trap?
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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?
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comfort zone
OPEN ACCESS TO RESEARCH
OPEN INNOVATION
OPEN EDU RESOURCES
KNOWLEDGE SHARING
ACADEMIC AUTONOMY
PUBLIC GOOD
LANGUAGE OF VALUES
dirty words
IMPACT
BRAND
COST BENEFIT ANALYSIS
METRICS
KPIs
BUSINESS CASES
LANGUAGE OF THE MARKET
[Data capture is not [Analytics] is not Metrics]
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DATA CAPTURE
The Data Exists Anyway
METRICS(come later)
ANALYTICS
Demystifying the role of data in decision-making
DECISIONS
EVIDENCEDECISION-MAKER(s)
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METRICS
“Evidence-based decision making”&
“Data-driven decision making”
DECISIONS
EVIDENCEMETRICS
VALUES
STRATEGIES
IMPACT MODELS STAKEHOLDER
VIEWS
ETC !
DECISION-MAKER(s)
RESOURCES
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Demystifying the role of data in decision-makingthe messy reality
“Evidence-informed& data-informed
decision making”
Demystifying data in an age of data
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LA
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UA
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OF
VA
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ES
LA
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UA
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OF
TH
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Opportunity:Using the techniques of the market to support our values
in the age of data
APIsFeeds
Web analyticsData visualisation
Storytelling
• 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
Tactics for responding to the age of data
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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
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Looking again:Social network use in education
A message and a medium
Social media as speaking (marketing)
Social media as listening (user feedback, market intelligence)
Social media as exchange (learning, scholarship, CRM?)
wikis as collaboration
student as media producer
practitioner peer to peer
amplification of teaching
amplification of events
broadcasting platforms e.g youtube
blogging as digital scholarship
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 ExamplesWho is the hashtag community?
Heart of #UKOER
http://zoom.it/6ucv5
By
Martin Hawksey UKOER Viz Project
My SNA ExamplesAre two people being listened to by the same people?
dkernohan & ambrouk
TwiangulateMutual Followers
Analysis
From www.twiangulate.com
Following 205 people in common of 1050 total tweeps followed
My SNA ExamplesAre two people listening to the same people?
dkernohan & ambrouk
TwiangulateMutual Friends
Analysis
From www.twiangulate.com
Followed by 244 people in common of 1336 total following tweeps
My SNA ExamplesA 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
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
Thank You