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Publication Type : Journal Article
Publisher : Springer-Nature
Source : Scientometrics. 113.1, 335-367
Url : https://link.springer.com/article/10.1007/s11192-017-2481-0
Campus : Amritapuri
Center : AmritaCREATE
Year : 2017
Abstract : As more and more interdisciplinary areas are emerging at a quick pace, analysis of interdisciplinary interactions among disciplines is of great importance. Citation network analysis is advancing as a tool to extricate policy implications from scientific as well as patent literature. Most of the studies related to interdisciplinarity under the lens of network analysis were concentrated mainly on journal–journal citation networks. Citation networks of articles reflect the accumulation as well as flow of knowledge. Therefore, specific developments that might cause interdisciplinary evolution can be identified. Due to this underexplored potential, we attempt to investigate interdisciplinarity at the level of published articles. As the interdisciplinary interactions among two disciplines is reflected by common/boundary papers and the arcs of cross-disciplinary citations, a quantitative methodology for assessing the strength of interdisciplinary interactions, dominant mode of interaction, mutual contribution, etc., is developed based on these. Interdisciplinary interactions among the fields ‘biotechnology for energy’ and ‘nanotechnology for energy’ is chosen as a case study. The existence of ‘mutual contribution’ among these fields is identified. ‘Biotechnology for energy’ is found to contribute more to the development of ‘nanotechnology for energy’ than vice versa. Important specific developments associated with interdisciplinary interactions are also explored using qualitative decision rules. Quantitative as well as qualitative methods devised in this paper form a framework for interdisciplinarity assessment that can be used by various decision makers.
Cite this Research Publication : Karunan, K., Lathabai, H. H., and Prabhakaran, T. (2017) “Discovering interdisciplinary interactions between two research fields using citation networks”. Scientometrics. 113.1, 335-367. https://doi.org/10.1007/s11192-017-2481-0