'Seed + expand' : a general methodology for detecting publication oeuvres of individual researchers

TY - JOUR

T1 - 'Seed + expand' : a general methodology for detecting publication oeuvres of individual researchers

AU - Reijnhoudt, Linda

AU - Costas, Rodrigo

AU - Noyons, Ed

AU - Börner, Katy

AU - Scharnhorst, Andrea

PY - 2014

Y1 - 2014

N2 - The study of science at the individual scholar level requires the disambiguation of author names. The creation of author's publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e.g., ORCID, VIVO, or DAI, author disambiguation remains a key problem when it comes to large-scale bibliometric analysis using data from multiple databases. This study introduces and tests a new methodology called seed + expand for semi-automatic bibliographic data collection for a given set of individual authors. Specifically, we identify the oeuvre of a set of Dutch full professors during the period 1980-2011. In particular, we combine author records from a Dutch National Research Information System (NARCIS) with publication records from the Web of Science. Starting with an initial list of 8,378 names, we identify 'seed publications' for each author using five different approaches. Subsequently, we 'expand' the set of publications in three different approaches. The different approaches are compared and resulting oeuvres are evaluated on precision and recall using a 'gold standard' dataset of authors for which verified publications in the period 2001-2010 are available.

AB - The study of science at the individual scholar level requires the disambiguation of author names. The creation of author's publication oeuvres involves matching the list of unique author names to names used in publication databases. Despite recent progress in the development of unique author identifiers, e.g., ORCID, VIVO, or DAI, author disambiguation remains a key problem when it comes to large-scale bibliometric analysis using data from multiple databases. This study introduces and tests a new methodology called seed + expand for semi-automatic bibliographic data collection for a given set of individual authors. Specifically, we identify the oeuvre of a set of Dutch full professors during the period 1980-2011. In particular, we combine author records from a Dutch National Research Information System (NARCIS) with publication records from the Web of Science. Starting with an initial list of 8,378 names, we identify 'seed publications' for each author using five different approaches. Subsequently, we 'expand' the set of publications in three different approaches. The different approaches are compared and resulting oeuvres are evaluated on precision and recall using a 'gold standard' dataset of authors for which verified publications in the period 2001-2010 are available.

KW - EINS

KW - TD1210

U2 - 10.1007/s11192-014-1256-0

DO - 10.1007/s11192-014-1256-0

M3 - Article

C2 - 25328257

SN - 0138-9130

VL - 101

SP - 1403

EP - 1417

JO - Scientometrics

JF - Scientometrics

IS - 2

ER -