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Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RELATED WORK
  5. METHOD
  6. PRELIMINARY RESULTS
  7. FUTURE WORK
  8. REFERENCES

In this ongoing study, I examine associations among scientists by analyzing scholarly publication data and Internet hyperlink relationships using a social network analysis framework. Unlike other studies of collaboration, this study does not start with an extant network of scientists who share a research focus, but rather groups who are networked for purposes of public and political engagement. I have chosen as my nodes two presumed “networks” of scientists: the group of 16 scientists who authored a January 27th', 2012 op-ed in The Wall Street Journal which suggested concerns about climate change were being exaggerated, and the group of 38 scientists who authored a response piece (supporting climate change science) on February 1st.

I have chosen climate science because of its scientific complexity that is of necessity interdisciplinary, and its scrutiny by non-expert publics. Building on the theoretical foundations of social epistemology, I examine how notions of the role of shared practices in engendering trust and knowledge-sharing among expert groups can be applied when the lines between expert and non-expert are contested in high-visibility public arenas. In exploring some of those questions, this study aims to discover if a social network methodology combining co-authorship data and hyperlink data can reveal patterns of association and engagement with traditional (e.g., scholarly publications) vs. non-traditional (e.g., web sites or blog articles) methods of communication and legitimation.

This study is intended as part of a larger research trajectory examining the role of social associations in influencing credibility and information trust decisions in areas where expert and non-experts must meet and negotiate shared meanings. These findings could suggest future directions for collaborative data sharing practices as well as support theoretical work in understanding how trust and credibility are granted in networked information environments.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RELATED WORK
  5. METHOD
  6. PRELIMINARY RESULTS
  7. FUTURE WORK
  8. REFERENCES

In a January 27th op ed in the Wall Street Journal, 16 scientists both questioned specific aspects of prevailing science around global climate change, and suggested the “international warming establishment” was deliberately suppressing the work of scientists who made “politically incorrect” claims that challenged the recommendations of the U.N.'s IPCC (“No need to panic about global warming; there's no compelling scientific argument for drastic action to ‘decarbonize’ the world's economy,”). The letter in response, from scientists who support widely-accepted climate change theories, repudiated many of the scientific claims made by the January 27th writers, and even questioned their expertise as scientists with enough relevant knowledge to comment on the question (“Check with climate scientists for views on climate,”).

The critics asserted that social and political pressures, including fears of not being promoted, kept many scientists from speaking about research findings that contradict prevailing climate science theories. The responding climate-change supporters also made a socially-influenced counter-argument stating that 97% of scientists “actively publishing” in the field of climate science agree with the human-caused global warming position.

There is substantial scholarly history that echoes the assertions of the letter writers in describing the social processes related to science work. Early science and technology scholars, such as Bruno Latour (Latour, 1986), established a foundational understanding of how science is “made” in shared practices. More recently, social science scholars have applied social epistemology theories to specialized science work such as high-energy physics (Knorr-Cetina, 1999) and biology (Star & Griesemer, 1989) to explain collaborative knowledge-sharing and trust. Information studies scholars further interpret these understandings in relation to information behaviors (Van House, 2003).

Within climate science in particular, many studies have looked at the social aspects of global warming science in terms of the organizational structure it fosters (Hulme & Mahony, 2010; Miller, 2001), or the discourses used in making claims or framing arguments (Carvalho, 2007; McCright & Dunlap, 2000). However, there has been little work on describing the relations between the actors in this socio-scientific conversation. The two sets of letter writers voluntarily associated with one another to engage with the public via the media in a way that is outside of the usual practices of science work. What provokes these associations? Are there (possibly predictive) relational patterns described by traditional scholarly or non-traditional networked methods of communication and legitimation? Are there actors outside the personal scientific network itself (political blogs, for example) that function “behind the scenes” to facilitate science communication and collaboration?

RELATED WORK

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RELATED WORK
  5. METHOD
  6. PRELIMINARY RESULTS
  7. FUTURE WORK
  8. REFERENCES

Climate science

Communications scholars frequently examine the mutually constitutive role of media discourse and ideology centered around climate change (Boykoff & Boykoff, 2004; Carvalho, 2007; McCright & Dunlap, 2003). Not surprisingly, understanding of climate change among members of the public continues to be profoundly compromised by polarized ideologies (Zia & Todd, 2010). Political orientations influence how opinions of climate science are formed among members of the general public, and trusted information comes most often from sources conforming to personal ideologies (Leiserowitz, Maibach, Roser-Renouf, Smith, & Dawson, 2010; Marquart-Pyatt et al., 2011).

Science and technology studies

Co-authorship analysis studies have suggested that authorship patterns in science journals may illustrate social patterns and patterns of practice within the discipline (Newman, 2001). Analysis of other forms of science documentation including emails (Ryghaug & Skjølsvold, 2010) and patents (Wuchty, Jones, & Uzzi, 2007) illustrate the important role of teams in the production of scientific knowledge, and how those teams negotiate shared understandings.

Information scientist John Budd (2007) applies a social epistemology approach to climate science specifically, and suggests that multiple epistemologies are at work in the disputes surround global climate change. Politics and ideology, well understood to thoroughly infuse this topic, form as much of a part of the “record” of global climate change as reports of expert scientists. When this dispute plays out in the media, journalistic norms of balance, may, in fact, present a bias towards those with more ideological or political motivations (Boykoff & Boykoff, 2004).

METHOD

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RELATED WORK
  5. METHOD
  6. PRELIMINARY RESULTS
  7. FUTURE WORK
  8. REFERENCES

For the initial stage of this project, I have used document-based data to identify network relationships. Subsequent stages of this research may involve interviews with scientist subjects to obtain more detailed social network data. I propose that a multi-modal approach, using both interview data and analysis of extant electronic documents, will provide a more complete picture of the network connections and functions.

Co-authorship Analysis

To develop the corpus describing an academic network, the 16 authors of the January letter and the 38 authors of the follow-up February piece were used as author search terms within the ISI Web of Science database. Some disambiguation was necessary for fairly common surnames.

I performed a frequency analysis and co-occurrence analysis using the Bibexcel system (Persson, Danell, & Wiborg Schneider, 2009). The group of 16 and the group of 38 were each analyzed separately, though an overall analysis of co-occurrence might be useful in later study.

Hyperlink Analysis

For my first analysis of hyperlink networks using the VOSON system (http://voson.anu.edu.au/) I supplied the “seed sites” for the initial web crawl. I discovered these seed sites with a Google search on each name of the letter writers from each Wall Street Journal letter. I selected a single site for each name based on the following criteria: it was a site under the author's control (not a Wikipedia entry, for example), either hosted by an institution or a personal site, and was among the first 4 results in a Google search. Secondary sources were consulted as needed for disambiguation. This initial process crawled two levels of links from the “seed” sites; deeper crawls might be used later.

PRELIMINARY RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RELATED WORK
  5. METHOD
  6. PRELIMINARY RESULTS
  7. FUTURE WORK
  8. REFERENCES

I am examining co-authorship data using NodeXL network analysis software; the resultant graphs initially display significant differences between the two groups. Figure 1 graphs the co-authorship network of climate science critics and shows almost no co-authorship activity (network density = .008).

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Figure 1. Co-authorship network of 16 climate science critics

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In contrast, Figure 2 shows a much more densely connected network among the climate science supporters (network density = .077). In both Figure 1 and 2, the node size corresponds to the total number of authorships, and the line weight indicates the number of collaborations.

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Figure 2. Co-authorship network of 38 climate science supporters

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Figure 3, below, is a preliminary graph of the crawl of sites linked to the climate science critics' pages. This directed graph (showing in-links and out-links) may have the potential to identify key network actors who do not operate within traditional science networks, but who nonetheless facilitate communication. (In the graph, the node size relates to the total number of in-links and out-links).

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Figure 3. Hyperlink network of climate science critics

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FUTURE WORK

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RELATED WORK
  5. METHOD
  6. PRELIMINARY RESULTS
  7. FUTURE WORK
  8. REFERENCES

Future work related to the specific application of this methodology to the climate science area will include further refinements to the web-crawling process. Ultimately, I hope to apply this methodology to more organic (and less event-driven) networks, and combine those findings with qualitative interview data.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. RELATED WORK
  5. METHOD
  6. PRELIMINARY RESULTS
  7. FUTURE WORK
  8. REFERENCES
  • Boykoff, M. T., & Boykoff, J. M. (2004). Balance as bias: Global warming and the US prestige press. Global Environmental Change, 14, 125136.
  • Budd, J. M. (2007). Information, analysis, and ideology: A case study of science and the public interest. Journal of the American Society for Information Science and Technology, 58(14), 23662371.
  • Carvalho, A. (2007). Ideological cultures and media discourses on scientific knowledge: Re-reading news on climate change. Public Understanding of Science, 16(2), 223243.
  • Check with climate scientists for views on climate (1 February 2012). The Wall Street Journal. from http://global.factiva.com/.
  • Hulme, M., & Mahony, M. (2010). Climate change: What do we know about the IPCC? Progress in Physical Geography, 34(5), 705718.
  • Knorr-Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Cambridge, MA: Harvard University Press.
  • Latour, B. (1986). Laboratory life: the construction of scientific facts. Princeton, N.J.: Princeton University Press.
  • Leiserowitz, A. A., Maibach, E. W., Roser-Renouf, C, Smith, N., & Dawson, E. (2010). Climategate, public opinion, and the loss of trust [Working paper]. Unpublished manuscript.
  • Marquart-Pyatt, S. T., Shwom, R. L., Dietz, T., Dunlap, R. E., Kaplowitz, S. A., McCright, A. M., et al. (2011). Understanding public opinion on climate change: A call for research. Environment: Science and Policy for Sustainable Development, 53(4), 3842.
  • McCright, A. M., & Dunlap, R. E. (2000). Challenging global warming as a social problem: An analysis of the conservative movement's counter-claims. Social Problems, 47(7), 499522.
  • McCright, A. M., & Dunlap, R. E. (2003). Defeating Kyoto: The conservative movement's impact on U.S. climate change policy. Social Problems, 50(3), 348373.
  • Miller, C. (2001). Hybrid Management: Boundary Organizations, Science Policy, and Environmental Governance in the Climate Regime. Science, Technology & Human Values, 26(4), 478500.
  • Newman, M. E. J. (2001). Scientific collaboration networks. I. Network construction and fundamental results. Physical Review E, 64(1), 016131.
  • No need to panic about global warming; there's no compelling scientific argument for drastic action to ‘decarbonize’ the world's economy (27 January 2012). The Wall Street Journal. from http://global.factiva.com/.
  • Persson, O. D., Danell, R., & Wiborg Schneider, J. (2009). How to use Bibexcel for various types of bibliometric analysis. In F. Aström, R. Danell, B. Larsen & J. Schneider (Eds.), Celebrating scholarly communication studies: A Festschrift for Olle Persson at his 60th Birthday (pp. 924). Leuven, Belgium: International Society for Scientometrics and Informetrics.
  • Ryghaug, M., & Skjølsvold, T. M. (2010). The Global Warming of Climate Science: Climategate and the Construction of Scientific Facts. International Studies in the Philosophy of Science, 24(3), 287307.
  • Star, S. L., & Griesemer, J. R. (1989). Institutional Ecology, Translations' and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907–39. Social Studies of Science, 19(3), 387420.
  • Van House, N. A. (2003). Digital libraries and collaborative knowledge construction. In A. P. Bishop, N. A. Van House & B. P. Buttenfield (Eds.), Digital library use: Social practice in design and evaluation (pp. 271293). Cambridge, Massachusetts: The MIT Press.
  • Wuchty, S., Jones, B. F., & Uzzi, B. (2007). The increasing cominance of teams in production of knowledge. Science, 3/5(5827), 10361039.
  • Zia, A., & Todd, A. M. (2010). Evaluating the effects of ideology on public understanding of climate change science: How to improve communication across ideological divides? Public Understanding of Science, 19(6), 743761.