Overview of my dissertation research on communication in science and the role of social computing technologies

1. The role of new
Information and
Communication
Technologies (ICTs) in
information and
communication in
science
A conceptual framework and empirical study
Christina K. Pikas
PhD Candidate
November 26, 2013

2. Agenda
• The Problem
• My Framework
• Testing the Framework
• Early Results
• Conclusions

3. The Problem
• “Communication is the essence of science”
(Garvey, 1979)
• Many scientists use social computing
technologies to communicate

4. Problem: Separate
Literatures
• Separate large bodies of literature studying
communication in science
• Communication, Journalism, and Rhetoric
• Information Science
• Science and Technology Studies
• These bodies are independent
(rarely citing each other)
• New studies of social computing technologies (SCT)
cite little of this literature

5. Problem: SCTs Evolve
Quickly
• New descriptive studies often narrowly focus
on a single technology
• Users adapt technologies as they adopt them
(Rogers, 2003)
• The uses and features of SCTs can evolve
quickly as they are adopted
• Studies of SCTs can get dated quickly

6. Needed: Comprehensive
Framework
• No overall view of how these SCTs fit into
what we already know about how scientists
communicate
• No grounded approach to understanding any
new SCT that comes along

7. My approach
Develop a comprehensive framework to
describe communication in science
that draws upon the relevant literatures
The framework will be useful for:
• Situating new technologies
• Research on uses of SCTs
• Helping organizations understand SCTs, so that
they may support their use

8. Agenda
• The Problem
• My Framework
• Testing the Framework
• Early Results
• Conclusions

9. Elements of the Framework
•
•
•
•
Features of the Communication Partners
Purposes of the Communication Activity
Features of the Message or Content
Features of the Channel

10. Partners
• Communication depends on the relationship
among the communication partners
(Schramm, 1971;Rogers & Kincaid, 1981)
• In SCTs, it might be imagined audience based
on cues (Marwick & boyd, 2011)

11. Partners: Numbers
• One to One
• One to Many

12. Partners:
Specialization/Sophistication
Each partner belongs to a category/level:
1. Participants in the specific research area who
share background knowledge, expertise, and
experience (Fleck, 1935; Kuhn, 1962;
Crane, 1972; Collins, 1985)
2. Other scientists in the general research area
with significant commonalities, but without
the specific expertise and experience of direct
participants (Paul, 2004)

13. Partners:
Specialization/Sophisticatio
n
3. Scientists and non-scientists who have some
college-level scientific training and who are
interested in science (Kyvik, 2005);
practitioners in an applied area of that science
who have strong experiential knowledge, but
who may have had less formal science
education (Fleck, 1935; Wynne, 1995)

14. Partners:
Specialization/Sophisticatio
n
4. Non-scientists who have an interest in science
(Kyvik, 2005)
5. Non-scientists who are not interested in
science and who may be distrustful of
scientists or some scientific ideas
(Merton, 1973)

15. Partners: Relationship
• Match by specialization/sophistication
• Social relationship
• Do they share a common background?
• Have they worked together long? (Kouzes, 2000)

16. Elements of the Framework
• Partners
• Purposes
• Content
• Channel

17. Purposes
To do with the intended goal or result
• Dissemination – to disseminate the results of
their work
• Discourse or contributing to the conversation
(Nentwich, 2003)
• Societal benefit or application (Kleinman, 1998)
• Identity (Polanyi, 2000)
• Rewards (Latour & Woolgar, 1986; Borgman &
Furner, 2002)
• Certification (Borgman, 2007; Nentwich, 2003;
Zuckerman & Merton, 1971)
• Preservation (Bowker, 2000)

18. Purposes
• Learning, teaching, or providing instruction
(Collins, 1985; Hara, Shapin, 1995;Solomon, Kim, &
Sonnenwald, 2003)
• Persuasion – e.g., grant applications but also
in journal articles (Latour & Woolgar, 1986)
• Evaluation or opinion – e.g., peer review
reports, grant review reports (Weller, 2001)

19. Purposes
• Coordination – socially to meet or to
negotiate research collaborations
(Vetere, Smith, & Gibbs, 2009)
• Social
• Common ground (Clarke & Brennan, 1993)
• Group membership (Tufekci, 2011)
• Politeness, social norms (Schneider, 1988)
• Entertainment – to entertain or provide
humor (Pikas, 2008)

20. Elements of the Framework
• Partners
• Purposes
• Content
• Channel

21. Content
Preliminary classification
• Topic
• Type
• Data
• Methods, algorithms, protocols, scripts
• Analysis, narrative
• Theoretical or philosophical
• Opinion or evaluation

22. Content
• Structure – well-structured (as in headings or
as in marked up for computational use) to
free text
• Persistence – part of the permanent record
or a short-lived utterance
• Review or quality control - extent to which
the communication is reviewed, edited, or
curated prior to or after transmission

23. Elements of the Framework
• Partners
• Purposes
• Content
• Channel

24. Channel
Elsewhere channel can mean source or format
but here used for medium between
communication partners
• Face to face
• Mediated – Clark and
Brennan, 1993, characteristics plus
coherence (Honeycutt & Herring, 2009)

25. Agenda
• The Problem
• My Framework
• Testing the Framework
• Early Results
• Conclusions

26. Study Setting
• One general area of science: geosciences
• Two SCT: Twitter and blogs

27. Why Geosciences
• Studies all aspects of earth and planetary
science including, for
example, geology, oceanography, and
climatology
• Active Twitter and blog communities
• Professional society support for social media
• Active local community
(NASA, USGS, APL, UM)

28. Methods
• Longitudinal study: 2010-2013
• Participants: Geoscientists who attend
American Geophysical Union conferences
• Tweets with hashtags:
#AGU10, #AGU11, #AGU2011, #AGU12, #AGU2
012, #AGU13, #AGU2013

29. Methods
Two ethnographic case studies:
• Directed qualitative content analysis (Hsieh
& Shannon, 2005) of tweets and blog
content
• Semi-structured interviews with participants
(Rubin & Rubin, 2005)
• Participant observation
• Some exploratory social network analysis for
selection of interview participants

30. More About Methods
• Retrieved tweets using a variety of methods
• Which tweets?
• Organizations (individuals representing
organization) – quite different behavior > omitted
• Many (modified tweet) MT and (retweets) RT are
for event and press release announcements >
omitted from content analysis
• Interview participants selected from meeting
tweeters
• Blogs/bloggers will be selected from the same
pool

31. Agenda
• The Problem
• My Framework
• Testing the Framework
• Early Results
• Conclusions

32. Exploratory SNA
• Networks from @ conversations
n1 tweets @n2 forms an arc
• Largest component shown
• Nodes sized by degree

33. 2010
setiinstitute
theagu
nasa
nasajpl
efectos1260
Twitter @ network, nodes sized by degree, largest component only
860 tweeters, 2995 tweets (whole conference)

34. 2011
Twitter @ network, nodes sized by degree, largest component only.
907 tweeters, 3604 tweets (whole conference)

35. 2012
Twitter @ network, nodes sized by degree, largest component only
1276 tweeters, 6207 tweets (whole conference)

36. Partners: Specialization
• Reported that it is good for outreach
“it’s clearly been useful for NASA in terms of their
missions “
• Yet most useful examples were
• Within research area
“there are times when one of us will have a
question, ‘hey I’m looking up …what’s the fraction of
Kuiper belt objects with satellites?’”
• With scientists from adjacent research areas
“…a way to bounce things off of people … ‘hey this is
how I’m interpreting this’ and [] who’s a dynamics guy
could say … ‘that’s kind of crazy and here’s why. Here’s
this paper that I’m working on that shows that this isn’t
what’s going on’”

37. Partners: Relationship
• Meet-ups and following relationships make
for groups or cliques with more
conversations and re-tweets – even if anyone
and everyone can observe threads

38. Purpose: Dissemination
• Session Reporting
• Example:
“Emile-Geay: using non-marine proxies for SST
reconstruction potentially problematic; unstable
teleconnections #AGU12”
• Coordination with multiple tweeters for
coverage of small conferences or for session
coverage

39. Purposes: Dissemination
• Sharing work in progress, links to slide decks
and poster files for conferences
“The DIL team's presentation at #agu2012 is now available
via slideshare”

40. Purposes
• Preservation: Use as notes
“it’s sort of become how I take notes now so it’s kind of
become a public note-taking thing”
• Teaching: Ask a scientist
• Persuasion: Effort to restore funding for
robotic planetary science missions

41. Purposes
• Coordination
• “Room for @chasingice showing at 7.30 is full! Moscone
South 300. #AGU12”
• Meet me at poster #1987 in Moscone South Hall C
11am-12pm, 1:40-2:00 pm, 2:15-3:45 pm. #AGU2012
• Social: Phatic (Vetere et al., 2009)
• “Postdoc bought a 5# bag of jelly beans to help him
through #AGU12 prep. I am now an attentive
advisor, stopping by his office every 5 min.”
• “@seagirlreed Christy, we miss you at #AGU2012. Naomi
made it. Ever again for you??
• “there’s a lot of the equivalent of sitting around the
dorm late at night shooting the breeze”

42. Content
• Evaluation/Opinion:
• Great little animation by @jimcameron to finish the
session. What a lander and deep ROV for Europa might
look like #agu12 #agu2012
• Impassioned lecture on latest climate science and
implications for policy by Bob Watson at #AGU2012.
Worth watching: http://bit.ly/QIkj2p
• Interviewees alluded to:
• Data
• Methods/Algorithms
• Quality control: press release tweets from
organizations approved

43. Content
• Analysis:
• “when the Chelyabinsk bolide happened that was really
exciting and I felt like I was able to go and get online and
I knew the tools and I was able to go: just based on this
video that we’re seeing the bolide the original body was
probably this big. That means it happens about this
often”

44. Conclusions
• As more geoscientists adopt Twitter, it
becomes more used/useful for informal
scholarly communication
• Interesting conversations in public – reveals
scientific work to non-scientists
• Science writers and science enthusiasts are
welcomed and engaged
• Flexibility with data collection is a must as
APIs change!

45. Take Aways
• Framework is useful to describe how
geoscientists use Twitter

46. Contact:
Christina K. Pikas
cpikas@umd.edu or cpikas@gmail.com
@cpikas
Slides will be posted to SlideShare
http://www.slideshare.net/cpikas

47. Clark & Brennan (1993) on
mediated channels
• Copresence refers to actually being in the same place at the same time.
• Visibility means that the conversation partners can see each other
including gestures and facial expressions.
• Audibility means that the conversation partners can hear each other
and the tone of voice.
• Cotemporality means that the messages from one person in the
conversation to another are received immediately.
• Simultaneity means that both parties can send and receive at exactly
the same time.
• Sequentiality refers more to recorded channels. It means that turns by
each partner do not get out of order.
• Reviewability enables conversation partners to look at what has been
said.
• Revisability enables conversation partners to correct or change what
they have said
• Coherence the ability of the channel to support “sustained, topicfocused, person-to-person exchanges” (Honeycutt & Herring, 2009, p.
2)