Abstract
In order to explore new scientific and innovative communities, analyses based on a technological infrastructure and its related tools, for example, ‘Web of science’ database for Scientometric analysis, are necessary. However, there is little systematic documentation of social media data and webometric analysis in relation to Korean and broader Asian innovation communities. In this short communication, we present (1) webometric techniques to identify communication processes on the Internet, such as social media data collection and analysis using an API-based application; and (2) experimentation with new types of data visualization using NodeXL, such as social and semantic network analysis. Our research data is drawn from the social networking site, Twitter. We also examine the overlap between innovation communities in terms of their shared members, and then, (3) calculate entropy values for trilateral relationships.
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Notes
While all replies are mentions, not all mentions are replies (Barash and Golder 2010). Replies are shown to third parties only when they follow both users, i.e., the one who sent the Tweet and the other who replied.
For a more detailed explanation, please refer to the full Wikipedia entry http://en.wikipedia.org/wiki/Application_programming_interface.
For detailed information about the FullText software, please visit http://www.leydesdorff.net/software/fulltext/index.htm.
CONCOR correlates each pair of actors in terms of the vector of similarities and partitions data into different groups based on these correlations. For detailed explanation, please see http://www.faculty.ucr.edu/~hanneman/nettext/C13_%20Structural_Equivalence.html#concor.
This period was selected as being the most recent date which was not affected by national holidays and/or vacation seasons.
According to Java et al. (2007), Twitter users can be categorized into three groups—information providers, friends, and information seekers—based on the number of followers and followings.
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Acknowledgments
The authors are grateful to colleagues in the WCU Webometrics Institute for their valuable comments on an earlier version of this paper that was presented at the SunBelt Social Networks Conference in February 2011, prior to extensive modification with different research questions. This research was partly supported by the WCU (World Class University) program of the National Research Foundation of Korea, funded by the Ministry of Education, Science and Technology (No. 515-82-06574) (http://www.webometrics.yu.ac.kr).
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Choi, S., Park, Jy. & Park, H.W. Using social media data to explore communication processes within South Korean online innovation communities. Scientometrics 90, 43–56 (2012). https://doi.org/10.1007/s11192-011-0514-7
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DOI: https://doi.org/10.1007/s11192-011-0514-7