Social Media and Student Learning: Using Analytics to Visualise Twitter Communication in the Classroom

Social Media and Student Learning: Using Analytics to Visualise Twitter Communication in the Classroom Sharon Stoerger PELC11 April 7, 2011 [email_address]

Agenda
Social media
What is it & why is it valuable?
Why Twitter?
Information visualisation
What is it?
Why should I visualise?
What are educational uses of information visualisation?
Visualising Twitter data
The future

What is social media?

One Definition (boyd & Ellison, 2007)
Web-based services that allow individuals to:
construct a public or semi-public profile within a bounded system;
articulate a list of other users with whom they share a connection ; and
view and traverse their list of connections and those made by others within the system.
http://jcmc.indiana.edu/vol13/issue1/boyd.ellison.html

Why is social media valuable?
Increase communication
Increase feelings of connectivity
Increase online learning community
Increase learning

http://twitter.com

Why Twitter?
Microblogging (140 characters)
Easy-to-use
Push down communication
Not email
Zero clutter
Students  social media > email (Roblyer et al., 2010)
Personal Learning Network (PLN)
Learning through connections
Connectivism (Siemens, 2004)

Definitions (Card et al., 1999, p. 7)
Visualisation:
The use of computer-based, interactive visual representations of data to amplify cognition.
Information visualisation:
The use of interactive visual representations of abstract, nonphysically based data to amplify cognition.

What is information visualisation?
Robertson, Card, & Mackinlay (1989)
First use of the term “information visualisation”
Cognitive amplification, interactivity, animation
Represent data – visual form
External cognition aids
Maps, charts, graphs, diagrams
Text clouds, animations
Social media relationships (e.g., Hansen, 2011)
Mashups (e.g., Google Maps/Google Earth)

“ Evolution” of Information Visualisation

Information Visualisation = Mainstream
Today’s tools
Free, interactive
Bring data to non-experts
Journalists
NY Times
http://tinyurl.com/45md7ur
Artists
Brooke Singer
Databody
http://www.bsing.net/databody.pdf

Q: WHY SHOULD I VISUALISE?

A Picture is Worth 1,000 Words Pictures can attract attention faster than other media (Barnard, 1927)

Reference Model for Visualisation (Card et al., 1999, p. 17)

The Language of the Eye
The User Illusion (1999)
Sight  faster
Bandwidth
Computer network
Better understanding
Eye
Mind

http://www.octium.eu/en/index.php/information-systems

TMI: Too Much Information
Twitter users (e.g., Rao, 2011)
572,000 accounts  created on March 12, 2011
460,000 (ave.) new accounts/day
Mobile users are up 182% from 2010
Tweets – the numbers
140 million Tweets (ave.)/day
50 million Tweets sent per day, a year ago
Record tweets = 177 million  March 11, 2011

Visualising Twitter Traffic http://vimeo.com/11302556

Visualisation = Data Compression
David McCandless, 2010
Data is the new oil
Or is data the new soil?
Fertile
Well-tilled medium
Visualisations = data flowers

Education-related Reasons to Visualise
Insight (not pictures)
New way to see & experience information
Hidden patterns, connections = revealed
Narrative = clarified
Amplify cognition - sense making (Card et al., 1999; Larkin & Simon, 1987)
Self-organising maps = brain organisation
Integrate offline-online experiences
Digital & critical competencies
Image: http://www.brainandlearning.eu/

Information Visualisation Example
Ward Shelley’s “History of Science Fiction”
Rhetorical drawings
http://scimaps.org/submissions/7-digital_libraries/maps/thumbs/024_LG.jpg

Visualisation Activities
Reimagine existing assignments
“ Software Studies” (Manovich, 2008)
Use & evaluate software
Limitations & biases
Influence
Analyse and produce visualisations
Visual literacy
Functional literacy (Selber, 2004)

What Twitter information can I visualise?
Twitter
Tweets (e.g., @csoleil)
Hashtags (e.g., #socmedia)/backchannel communication
Retweets
Replies
Links
Projects
Text
Personal data
Social data
Create = digital artifacts

HOW DO I VISUALIZE TWITTER DATA?

Text clouds: Wordle http://www.wordle.net/
Common text visualiser
“ A toy for generating word clouds”

Text Cloud: Tagxedo http://www.tagxedo.com/

Text & Hashtag Clouds: TweetStats http://tweetstats.com/

Wordle Plus: Many Eyes http://www-958.ibm.com/software/data/cognos/manyeyes/
“… like Facebook for infovis nerds” (Sorapure, 2009, p. 63)
IBM researchers (Fernanda Viegas, Martin Wattenberget, etc.)

Text Analysis Portal for Research (TAPoR) http://portal.tapor.ca/portal/portal
Tools  analysis and retrieval
Representative texts  experimentation

Conversations: Twitterfall http://twitterfall.com/
Real time tweet searching
New tweets fall on the page
Pause tweets

Statistics: TweetStat http://tweetstats.com/

Networks: Mentionmap http://apps.asterisq.com/mentionmap/#

Twitter Friends Network Browser http://www.neuroproductions.be/twitter_friends_network_browser/

Visualisation Concerns
“ Eye candy”
“ Chart junk” graphics (Card et al., 1999)
Graphical distortion - highlights anomalies (Tufte, 1983)
Ease-of-use
Less familiar with data sets
Not fully understand data
Mislead/confuse consumers
Evaluation of effectiveness
Criteria, measurements, methods???
Experience subjectivity

Rashômon (4 versions of the truth)
http://www.youtube.com/watch?v=xCZ9TguVOIA

What’s Next?
Programs
National Visual Analytics Centers (NVACs) - 2005
Analyse agency information needs
Disciplines
Technology, art, science (van Wijik, 2005)
Humanities
Education
Tools
Dashboards, visual analytics, simple graphs
Interactive visualisations
Mobile applications  Public participation

The Future? http://www.rottentomatoes.com/m/minority_report/trailers/11129681

Thank You!!!
Questions?
Sharon Stoerger
Email: [email_address]
Facebook: sharon.stoerger
Twitter: csoleil
Second Life: Cerulean Soleil

Read More About It
Card, S. K., Mackinlay, J. D., Shneiderman, B. (1999). Readings in information visualization . San Francisco, CA: Morgan Kaufmann Publishers, Inc.
Few, S. (2010). Information visualization, design and the arts: Collision or collaboration? Visual Business Intelligence Newsletter.
Johnson, L., Levine, A., Smith, R., Stone, S. (2010). The 2010 horizon report. Austin, TX: The New Media Consortium.
Larkin, J., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11 (1), 65-99.
Manovich, L. (2010). What is visualization. http://manovich.net/2010/10/25/new-article-what-is-visualization/
Moretti, F. (2005). Graphs, maps, trees: Abstract models for a literary history . London: Verso
Sorapure, M. (2009). Information visualization, Web 2.0, and the teaching of writing. Computers and Composition, 27, 59-70.
Tufte, E. R. (1983). The visual display of quantitative information . Cheshire, CT: Graphic Press.
van Wijk, J. J. (2005). The value of visualization. In C. Silva, E. Groeller, H. Rushmeier (eds .), Proceedings of IEEE Visualization 2005 , 79-86.
Ware, C. (2004). Information visualization: Perception for design, 2nd ed. San Francisco: Morgan Kaufmann Publishers, Inc.

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