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 StoergerPELC11April 7, [email protected]

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 Traffichttp://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: Tagxedohttp://www.tagxedo.com/

Text & Hashtag Clouds: TweetStatshttp://tweetstats.com/

Wordle Plus: Many Eyeshttp://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: TweetStathttp://tweetstats.com/

Networks: Mentionmaphttp://apps.asterisq.com/mentionmap/#

Twitter Friends Network Browserhttp://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 protected]: sharon.stoergerTwitter: csoleilSecond 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.