A relational altmetric? Network centrality on ResearchGate as an indicator of scientific impact
Social media are becoming increasingly popular in scientific communication. A range of platforms, such as academic social networking sites (SNS), are geared specifically towards the academic community. Proponents of the altmetrics approach have pointed out that new media allow for new avenues of sci...
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| Published in | Journal of the Association for Information Science and Technology Vol. 67; no. 4; pp. 765 - 775 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Blackwell Publishing Ltd
01.04.2016
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2330-1635 2330-1643 |
| DOI | 10.1002/asi.23423 |
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| Abstract | Social media are becoming increasingly popular in scientific communication. A range of platforms, such as academic social networking sites (SNS), are geared specifically towards the academic community. Proponents of the altmetrics approach have pointed out that new media allow for new avenues of scientific impact assessment. Traditional impact measures based on bibliographic analysis have long been criticized for overlooking the relational dynamics of scientific impact. We therefore propose an application of social network analysis to researchers' interactions on an academic social networking site to generate potential new metrics of scientific impact. Based on a case study conducted among a sample of Swiss management scholars, we analyze how centrality measures derived from the participants' interactions on the academic SNS ResearchGate relate to traditional, offline impact indicators. We find that platform engagement, seniority, and publication impact contribute to members' indegree and eigenvector centrality on the platform, but less so to closeness or betweenness centrality. We conclude that a relational approach based on social network analyses of academic SNS, while subject to platform‐specific dynamics, may add richness and differentiation to scientific impact assessment. |
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| AbstractList | Social media are becoming increasingly popular in scientific communication. A range of platforms, such as academic social networking sites (SNS), are geared specifically towards the academic community. Proponents of the altmetrics approach have pointed out that new media allow for new avenues of scientific impact assessment. Traditional impact measures based on bibliographic analysis have long been criticized for overlooking the relational dynamics of scientific impact. We therefore propose an application of social network analysis to researchers' interactions on an academic social networking site to generate potential new metrics of scientific impact. Based on a case study conducted among a sample of Swiss management scholars, we analyze how centrality measures derived from the participants' interactions on the academic SNS ResearchGate relate to traditional, offline impact indicators. We find that platform engagement, seniority, and publication impact contribute to members' indegree and eigenvector centrality on the platform, but less so to closeness or betweenness centrality. We conclude that a relational approach based on social network analyses of academic SNS, while subject to platform‐specific dynamics, may add richness and differentiation to scientific impact assessment. |
| Author | Meckel, Miriam Lutz, Christoph Hoffmann, Christian Pieter |
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Seglen, P.O. (1997). Why the impact factor of journals should not be used for evaluating research. BMJ British Medical Journal, 314(7079), 498-502. Watts, D.J., & Strogatz, S.H. (1998). Collective dynamics of "small-world" networks. Nature, 393(6684), 440-442. Bik, H.M., & Goldstein, M.C. (2013). An introduction to social media for scientists. PLoS Biology, 11(4), e1001535. Retrieved from http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001535 Hughes, D.J., Rowe, M., Batey, M., & Lee, A. (2012). A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage. Computers in Human Behavior, 28(2), 561-569. Crane, D. (1972). Invisible colleges: Diffusion of knowledge in scientific communities. Chicago: University of Chicago Press. Kousha, K., Thelwall, M., & Rezaie, S. (2010). Using the web for research evaluation: The integrated online impact indicator. Journal of Informetrics, 4(1), 124-135. Thelwall, M. (2012). Journal impact evaluation: A webometric perspective. Scientometrics, 92(2), 429-441. Priem, J. (2013). Scholarship: Beyond the paper. Nature, 495, 437-440. Giglia, E. (2011). Academic social networks: It's time to change the way we do research. European Journal of Physical and Rehabilitation Medicine, 47(2), 345-350. Ewing, T. (2008). Participation cycles and emergent cultures in an online community. International Journal of Market Research, 50(5), 575-590. Quan-Haase, A., & Young, A.L. (2010). Uses and gratifications of social media: A comparison of Facebook and instant messaging. Bulletin of Science, Technology & Society, 30(5), 350-361. Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. Artificial Intelligence, 2(2), 361-362. Thelwall, M., Sud, P., & Wilkinson, D. (2012). Link and co-inlink network diagrams with URL citations or title mentions. 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Procter, R., Williams, R., Stewart, J., Poschen, M., Snee, H., Voss, A., ... (2010). Adoption and use of Web 2.0 in scholarly communications. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 368(1926), 4039-4056. Bourdieu, P. (1984). Distinction: A social critique of the judgement of taste. Cambridge, MA: Harvard University Press. Moody, J. (2004). The structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. American Sociological Review, 69(2), 213-238. Valenzuela, S., Park, N., & Kee, K.F. (2009). Is there social capital in a social network site? Facebook use and college students' life satisfaction, trust, and participation. Journal of Computer-Mediated Communication, 14(4), 875-901. Vaughan, L., & Shaw, D. (2003). Bibliographic and web citations: What is the difference? Journal of the American Society for Information Science and Technology, 54(14), 1313-1322. Yan, E., & Ding, Y. (2012). Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. Journal of the American Society for Information Science, 63(7), 1313-1326. Ellison, N.B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook "friends": Social capital and college students' use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143-1168. Thelwall, M., & Kousha, K. (2014b). Academia.edu: Social network or academic network? Journal of the Association for Information Science and Technology, 65(4), 721-731. Thelwall, M., & Harries, G. (2004). Do the web sites of higher rated scholars have significantly more online impact? Journal of the American Society for Information Science and Technology, 55(2), 149-159. Hirsch, J.E. (2007). Does the h-index have predictive power? Proceedings of the National Academy of Sciences of the United States of America, 104(49), 19193-19198. Nov, O., Naaman, M., & Ye, C. (2009). Analysis of participation in an online photo-sharing community: A multidimensional perspective. Journal of the American Society for Information Science and Technology, 61(3), 555-566. Bornmann, L. (2013). Is there currently a scientific revolution in scientometrics? Journal of the American Society for Information Science and Technology, 65(3), 647-648. boyd, d., & Ellison, N.B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge, MA: Cambridge University Press. Borgatti, S.P., Mehra, A., Brass, D.J., & Labianca, G. (2009). Network analysis in the social sciences. Science, 323(5916), 892-895. Koku, E., Nazer, N., & Wellman, B. (2000). Netting scholars: Online and offline. American Behavioral Scientist, 44(10), 1-19. PLoS Medicine Editors. (2006). The impact factor game. PLoS Medicine, 3(6), e291. Retrieved from http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0030291 Bourdieu, P. (1990). Homo academicus. Palo Alto, CA: Stanford University Press. Garfield, E. (2003). The meaning of the impact factor. International Journal of Clinical and Health Psychology, 3(2), 363-369. Shema, H., Bar-Ilan, J., & Thelwall, M. (2012). Research blogs and the discussion of scholarly information. PLoS One, 7(5), e35869. Retrieved from http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0035869 Priem, J., & Costello, K.L. (2010). How and why scholars cite on Twitter. Proceedings of the 73rd ASIST Annual Meeting, 1-4. Eysenbach, G. (2011). Can Tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. Journal of Medical Internet Research, 13(4), 1-15. 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| References_xml | – reference: Jeng, W., He, D., & Jiang, J. (2014). User participation in an academic social networking site: A survey of open group users on Mendeley. Journal of the Association for Information Science and Technology, forthcoming. – reference: Gruzd, A., & Goertzen, M. (2013). Wired Academia: Why social science scholars are using social media. Proceedings of the 46th Hawaii Conference on System Sciences, 3332-3341. – reference: Valenzuela, S., Park, N., & Kee, K.F. (2009). Is there social capital in a social network site? Facebook use and college students' life satisfaction, trust, and participation. Journal of Computer-Mediated Communication, 14(4), 875-901. – reference: Wellman, B., Quan-Haase, A., Witte, J., & Hampton, K. (2001). Does the internet increase, decrease, or supplement social capital?: Social networks, participation, and community commitment. American Behavioral Scientist, 45(3), 436-455. – reference: Bourdieu, P. (1996). The rules of art: Genesis and structure of the literary field. Palo Alto, CA: Stanford University Press. – reference: Nentwich, M., & König, R. (2012). Cyberscience 2.0-Research in the age of digital social networks. Frankfurt and New York: Campus. – reference: Desai, T., Shariff, A., Shariff, A., Kats, M., Fang, X., Christiano, C., & Ferris, M. (2012). Tweeting the meeting: An in-depth analysis of Twitter activity at Kidney Week 2011. PLoS One, 7(7), e40253. Retrieved from http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0040253 – reference: Shema, H., Bar-Ilan, J., & Thelwall, M. (2012). Research blogs and the discussion of scholarly information. PLoS One, 7(5), e35869. Retrieved from http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0035869 – reference: Ellison, N.B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook "friends": Social capital and college students' use of online social network sites. Journal of Computer-Mediated Communication, 12(4), 1143-1168. – reference: Eysenbach, G. (2011). Can Tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact. Journal of Medical Internet Research, 13(4), 1-15. Retrieved from http://www.jmir.org/2011/4/e123/ – reference: Hirsch, J.E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569-16572. – reference: boyd, d., & Ellison, N.B. (2007). Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210-230. – reference: Thelwall, M., & Kousha, K. (2014b). Academia.edu: Social network or academic network? Journal of the Association for Information Science and Technology, 65(4), 721-731. – reference: Nielsen, M. (2012). Reinventing discovery: The new era of networked science. Princeton, NJ: Princeton University Press. – reference: Thelwall, M. (2012). Journal impact evaluation: A webometric perspective. Scientometrics, 92(2), 429-441. – reference: Yan, E., & Ding, Y. (2012). Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. Journal of the American Society for Information Science, 63(7), 1313-1326. – reference: Borgatti, S.P., Mehra, A., Brass, D.J., & Labianca, G. (2009). Network analysis in the social sciences. Science, 323(5916), 892-895. – reference: Thelwall, M., Sud, P., & Wilkinson, D. (2012). Link and co-inlink network diagrams with URL citations or title mentions. Journal of the American Society for Information Science and Technology, 63(4), 805-816. – reference: Vaughan, L., & Shaw, D. (2003). Bibliographic and web citations: What is the difference? Journal of the American Society for Information Science and Technology, 54(14), 1313-1322. – reference: Giglia, E. (2011). Academic social networks: It's time to change the way we do research. European Journal of Physical and Rehabilitation Medicine, 47(2), 345-350. – reference: Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. Artificial Intelligence, 2(2), 361-362. – reference: Pénard, T., & Poussing, N. (2010). Internet use and social capital: The strength of virtual ties. Journal of Economic Issues, 44(3), 569-595. – reference: Yan, E., & Ding, Y. (2009). Applying centrality measures to impact analysis: A coauthorship network analysis. Journal of the American Society for Information Science, 60(10), 2107-2118. – reference: Moody, J. (2004). The structure of a social science collaboration network: Disciplinary cohesion from 1963 to 1999. American Sociological Review, 69(2), 213-238. – reference: Vaughan, L., & Hysen, K. (2002). Relationship between links to journal Web sites and impact factors. Aslib Proceedings, 54(6), 356-361. – reference: Kousha, K., Thelwall, M., & Rezaie, S. (2010). Using the web for research evaluation: The integrated online impact indicator. Journal of Informetrics, 4(1), 124-135. – reference: Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge, MA: Cambridge University Press. – reference: Bollen, J., Van De Sompel, H., Hagberg, A., & Chute, R. (2009). A principal component analysis of 39 scientific impact measures. PLoS ONE, 4(6), e6022. Retrieved from http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0006022 – reference: Procter, R., Williams, R., Stewart, J., Poschen, M., Snee, H., Voss, A., ... (2010). Adoption and use of Web 2.0 in scholarly communications. Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences, 368(1926), 4039-4056. – reference: Priem, J. (2013). Scholarship: Beyond the paper. Nature, 495, 437-440. – reference: Priem, J., & Costello, K.L. (2010). How and why scholars cite on Twitter. Proceedings of the 73rd ASIST Annual Meeting, 1-4. – reference: Garfield, E. (2003). The meaning of the impact factor. International Journal of Clinical and Health Psychology, 3(2), 363-369. – reference: Koku, E., Nazer, N., & Wellman, B. (2000). Netting scholars: Online and offline. American Behavioral Scientist, 44(10), 1-19. – reference: Hughes, D.J., Rowe, M., Batey, M., & Lee, A. (2012). A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage. Computers in Human Behavior, 28(2), 561-569. – reference: Watts, D.J., & Strogatz, S.H. (1998). Collective dynamics of "small-world" networks. Nature, 393(6684), 440-442. – reference: PLoS Medicine Editors. (2006). The impact factor game. PLoS Medicine, 3(6), e291. Retrieved from http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.0030291 – reference: Aguinis, H., Suárez-González, I., Lannelongue, G., & Joo, H. (2012). Scholarly impact revisited. Academy of Management Perspectives, 26(2), 105-132. – reference: Ewing, T. (2008). Participation cycles and emergent cultures in an online community. International Journal of Market Research, 50(5), 575-590. – reference: Nov, O., Naaman, M., & Ye, C. (2009). Analysis of participation in an online photo-sharing community: A multidimensional perspective. Journal of the American Society for Information Science and Technology, 61(3), 555-566. – reference: Freeman, L.C. (2004). The development of social network analysis-A study in the sociology of science. North Charleston, SC: Booksurge Llc. – reference: Priem, J., & Hemminger, B.H. (2010). Scientometrics 2.0: New metrics of scholarly impact on the social Web. First Monday, 15(7-5). – reference: Seglen, P.O. (1997). 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