| Yazarlar (3) |
Mehmet Ali Köseoğlu
Türkiye |
Doç. Dr. Hasan Evrim ARICI
Kastamonu Üniversitesi, Türkiye |
Doç. Dr. Nagihan ÇAKMAKOĞLU ARICI
Kastamonu Üniversitesi, Türkiye |
| Özet |
| Bibliometric scholars have primarily evaluated massive data without refining any potential typing and/or spelling errors, resulting in two constraints: misinterpretation of findings and misleading future research in the knowledge domain. Thus, this study aims to introduce the data curation approach in order to reduce these restrictions. Utilizing a renowned service journal (Journal of Service Research) as the study sample, we first acquired all published papers and then constructed raw and clean datasets. We ran citation and co-citation analyses on these datasets separately. Our investigation reveals that clean data yielded more trustworthy and valid results than raw data with redundant references. This study provides an answer to how and why data in bibliometric analysis needs to be cleaned. It thus contributes to the literature by suggesting a new route for scholars to improve the accuracy and reliability of their bibliometric findings. |
| Anahtar Kelimeler |
| Quantitative analysis | Cluster analysis | Longitudinal data analysis. |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | ESCI dergilerinde yayınlanan tam makale |
| Dergi Adı | COLLNET JOURNAL OF SCIENTOMETRICS AND INFORMATION MANAGEMENT |
| Dergi ISSN | 0973-7766 Wos Dergi |
| Dergi Tarandığı Indeksler | ESCI |
| Makale Dili | İngilizce |
| Basım Tarihi | 12-2023 |
| Cilt No | 17 |
| Sayı | 2 |
| Sayfalar | 269 / 287 |
| Doi Numarası | 10.47974/CJSIM-2020-0011 |
| Makale Linki | http://dx.doi.org/10.47974/cjsim-2020-0011 |
| Atıf Sayıları | |
| WoS | 3 |
| Google Scholar | 6 |
