Pikas casci talk 11262013 final

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

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  • Chu & Guo (2006), Mark Ware Consulting (2008), Proctor, Williams, & Stewart, (2010)
  • According to Rogers and Kincaid (1981), communication is “a process in which the participants create and share information with one another in order to reach a mutual understanding.” Communication is based on a relationship (Schramm, 1971)
  • At this level there are two subgroups
  • Communication with this group may vary if the scientist has training in public communication Dunwoody, Brossard, and Dudo (2009)
  • Jakobson (1960) states, “CONTACT, physical channel and psychological connection between the addresser and addressee” (p. 353).
  • Re-do in red
  • Goes in methods
  • In oral communication and social media that share many aspects of oral communication, much of the communication is phatic; that is, it is not primarily informational, rather it is used for social purposes such as establishing rapport and maintaining relationships and for purposes related to establishing and maintaining the communication channel (Vetere et al., 2009) or place in the social network (Miller, 2008)
  • Pikas casci talk 11262013 final

    1. 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. 2. Agenda • The Problem • My Framework • Testing the Framework • Early Results • Conclusions
    3. 3. The Problem • “Communication is the essence of science” (Garvey, 1979) • Many scientists use social computing technologies to communicate
    4. 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. 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. 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. 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. 8. Agenda • The Problem • My Framework • Testing the Framework • Early Results • Conclusions
    9. 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. 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. 11. Partners: Numbers • One to One • One to Many
    12. 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. 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. 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. 15. Partners: Relationship • Match by specialization/sophistication • Social relationship • Do they share a common background? • Have they worked together long? (Kouzes, 2000)
    16. 16. Elements of the Framework • Partners • Purposes • Content • Channel
    17. 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. 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. 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. 20. Elements of the Framework • Partners • Purposes • Content • Channel
    21. 21. Content Preliminary classification • Topic • Type • Data • Methods, algorithms, protocols, scripts • Analysis, narrative • Theoretical or philosophical • Opinion or evaluation
    22. 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. 23. Elements of the Framework • Partners • Purposes • Content • Channel
    24. 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. 25. Agenda • The Problem • My Framework • Testing the Framework • Early Results • Conclusions
    26. 26. Study Setting • One general area of science: geosciences • Two SCT: Twitter and blogs
    27. 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. 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. 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. 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. 31. Agenda • The Problem • My Framework • Testing the Framework • Early Results • Conclusions
    32. 32. Exploratory SNA • Networks from @ conversations n1 tweets @n2 forms an arc • Largest component shown • Nodes sized by degree
    33. 33. 2010 setiinstitute theagu nasa nasajpl efectos1260 Twitter @ network, nodes sized by degree, largest component only 860 tweeters, 2995 tweets (whole conference)
    34. 34. 2011 Twitter @ network, nodes sized by degree, largest component only. 907 tweeters, 3604 tweets (whole conference)
    35. 35. 2012 Twitter @ network, nodes sized by degree, largest component only 1276 tweeters, 6207 tweets (whole conference)
    36. 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. 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. 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. 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. 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. 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. 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. 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. 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. 45. Take Aways • Framework is useful to describe how geoscientists use Twitter
    46. 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. 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)

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