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The Brave New World of
Social Communication: Exploring Patterns of Opinion
Dissemination in Twitter
Kristin Runge
Dominique Brossard
Dietram A. Scheufele
Department of Life Sciences Communication
Michael Xenos
Department of Communication Arts
In Conjunction With
Ashley Anderson, Michael Cacciatore, Doo-hun Choi,
Jiyoun Kim, Nan Li, Xuan Liang, Maria Stubbing, Leona
Yi-Fan Su, Sara Yeo
University of Wisconsin
Nanoscale Science & Engineering Center
Department of Life Sciences Communication
Department of Communication Arts
Why Nanotechnology?
Why Nanotechnology?
Why Twitter?
Role of Twitter in Arab Spring, 2010
Downed U.S. Airways flight, 2009
Mumbai bomb blasts, 2008
What’s going on?
Christensen, C. (2011). Twitter revolutions? Addressing social media dissent. The Communication Review 14(3) 155 – 157. DOI 10.10880/10714421.2011.59735
Lasorsa, D.L., Lewis, S.C., Holton, A.E. (2011). Normalizing Twitter: Journalism practice in an emerging communication space. Journalism Studies 1 (1), 1 – 18. DOI
10.1080/145150X.571825.
Murthy, D. (2011). Twitter: Microphone for the masses? Media Culture Society 33(5) 779 – 789. DOI: 10.1177/0163443711404744
Hughes, A.L. & Palen, L. (2009) Twitter adoption and use in mass convergence and emergency events. International Journal of Emergency Management 6(3-4) 248
– 260. DOI 10.150/IJEM.2009.031564
Broad Research Questions
Will opinion valence be discernible for
nanotechnology subject Twitter posts?
Are geographic areas close to technology centers
and with populations fitting the profile of science
internet users likely to have higher incidences of
nanotechnology posts?
Will opinion volume vary over time?
Methodology
Crimson Hexagon ForSight
Automatic non-parametric content analysis
software
Inter-related groups of coders
Tested for reliability and validity
September 1, 2010 – August 31, 2011
N=495,195
Hopkins, D.J., King, G. (2010 ) A method of automated nonparametric content analysis for social science. American Journal of Political Science,54(1) 229 – 247
Porter AL, Youtie J, Shapira P, Schoeneck DJ (2008) Refining search terms for nanotechnology. Journal of Nanoparticle Research 10(5):715–728.
Sentiment Coding
Optimistic
Certain
Pessimistic
Certain
Neutral
Uncertain
Opinion Valence
Geographic Distribution
National Science Foundation Funded
Nanotechnology Research Centers
High Low
Opinion Over Time
4217
6235
0
1000
2000
3000
4000
5000
6000
7000 Relevant opinions
Relevant
opinions
4217
6235
0
1000
2000
3000
4000
5000
6000
7000 Relevant opinions
Relevant
opinions
In New York:
Argonne Scientists
Watch Rebirth of
Nanoparticles
In Texas
Exploring Nanotech
Anti Infective Agent
for Soldier's Wounds
In California
Caltech French
Research Team on
Nanotech
Commercialization
36.5%
Traffic in
CA, TX
& NY
Conclusions
Low levels of nanotechnology volume relative to
overall number of daily tweets
Nano opinion volume correlates with nano news
Valence is relatively more certain, relatively less
pessimistic
Observing the Nanotechnology Twitterati
Future Research:
Nanotechnology Twitterati?
Relatively well informed
Higher interest in nanotechnology news
Using Twitter to communicate with other members
of nanotechnology research community
Younger and/or more innovation-oriented in
communication and networking tools
Limitations
Automated nonparametric software 1.0
Responsive, but still a black box
Recall limit of 1,000 posts per query
Language tricky
Sarcasm is soooo easy to detect. Really.
Initial training time consuming
Good results take time, and lots of it
Kristin Runge
Life Sciences Communication
(608) 850-9005
Dominique Brossard
Dietram A. Scheufele
Michael Xenos
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