Jinseok Kim defends dissertation

Posted: April 25, 2017

Doctoral candidate Jinseok Kim successfully defended his dissertation, "The impact of author name disambiguation on knowledge discovery from large-scale scholarly data," on April 24. 

His committee included Assistant Professor Jana Diesner (chair), Associate Professor Catherine Blake, Assistant Professor Vetle Torvik, Michelle Shumate (associate professor of communication studies, Northwestern University), and Seok-Hyoung Lee (senior researcher, Korea Institute of Science and Technology Information).

From the abstract: In this study, I demonstrate that the choice of data pre-processing methods for resolving author name ambiguity can adversely affect our understanding of scholarly collaboration patterns and coauthorship network structure extracted from bibliometric data . . . A common challenge has been that author names in bibliometric data are not properly disambiguated: authors may share the same name (i.e., different authors are sometimes misrepresented to be a single author which can lead to a “merging of identities”). In addition, one author may use name variations (i.e., an author may be represented as two or more different authors which can lead to a “splitting of identities”). When faced with these challenges, most scholars have pre-processed bibliometric data using simple heuristics (e.g., if two author names share the same surname and given name initials, they are presumed to refer to the same author identity) and assumed that their findings are robust to errors due to author name ambiguity.

My findings show that initial-based name disambiguation methods can severely distort our understanding of given networks and such distortion gets severe over time. Moreover, this distortion can sometimes lead to false knowledge of network formation and evolution mechanisms such as preferential attachment generating power-law distribution of node degree and to false validation of theories about the choice of collaborators in scientific research, which may result in ill-informed decisions about research policy and resource allocation.

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