NDLI: Why name ambiguity resolution matters for scholarly big data research

Content Provider	IEEE Xplore Digital Library
Author	Jinseok Kim Diesner, J. Aleyasen, A. Heejun Kim Hwan-Min Kim
Copyright Year	2014
Description	Author affiliation: Sch. of Inf. & Libr. Sci., Univ. of North Carolina at Chapel Hill, Chapel Hill, NC, USA (Heejun Kim) \|\| Grad. Sch. of Libr. & Inf. Sci., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA (Jinseok Kim; Diesner, J.) \|\| Dept. of Comput. Sci., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA (Aleyasen, A.) \|\| Dept. of Overseas Inf., Korea Inst. of Sci. & Technol. Inf., Daejeon, South Korea (Hwan-Min Kim)
Abstract	This paper illustrates how data pre-processing choices about author name disambiguation can affect research findings about scholarly networks and hypotheses about underlying social mechanisms. We have analyzed three big scholarly datasets that were disambiguated algorithmically and via two common initial-based disambiguation methods; namely first-initial and all-initials disambiguation. The comparison of resulting bibliometric and network properties revealed that initial-disambiguation bears the prevalent risks of incorrectly merging author identities, underestimating the number of unique authors and inflating the average productivity and number of collaborators per author. The gaps between outcomes of name ambiguity resolution methods range from -4.23% to -87.36% per dataset for the number of unique authors, from 3.75% to 691.20% for average productivity, and from 5.06% to 285.28% for degree centrality for initial based methods compared to algorithmic disambiguation. This calls for special attention to data pre-processing choices in scholarly big data research.
Starting Page	1
Ending Page	6
File Size	755578
Page Count	6
File Format	PDF
ISBN	9781479956661
DOI	10.1109/BigData.2014.7004345
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Productivity Disambiguation Heuristic algorithms Bibliometrics Merging Collaboration Network analysis Educational institutions Big data
Content Type	Text
Resource Type	Article

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