Evaluating wider impacts of books via fine-grained mining on citation literatures
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Evaluating wider impacts of books via fine‑grained mining on citation literatures Qingqing Zhou1 · Chengzhi Zhang2 Received: 23 July 2019 © Akadémiai Kiadó, Budapest, Hungary 2020
Abstract Citations are commonly used to measure academic impacts of scientific publications, including books. However, citation frequencies of books are single numerical evaluation metrics. It neglects details about books (e.g. contents), which may lead to the decline in comprehensiveness of evaluation results. Hence, fine-grained mining on books’ citation information to integrate frequency metrics and content metrics can obtain more reliable evaluation results. Books’ citation literatures (i.e. literatures cited books) present citation frequencies of books, and reflect citation intentions, topics and domains simultaneously. Existing research focused on analysing citation frequencies, authors or citation contexts of citation literatures to conduct citation analysis. It may be costly for collecting citation contexts and neglected latent information of citation literatures, such as impact scopes or topics of books reflected by citation literatures. Therefore, in this paper, we conducted finegrained analysis on books’ citation literatures to assess whether citation literatures could be systematically used for indicators of books’ wider impacts. Specifically, we firstly collected books and corresponding information about their citation literatures. Then, we extracted multi-dimensional metrics via multi-granularity mining on citation literatures, and got assessment results by integrating content-level and frequency-level metrics. Finally, we compared assessment results based on citation literatures and existing metrics for assessing books’ impacts to verify assessment results. Experimental results infer that citation literatures are a promising source for book impact assessment, especially books’ academic impacts. Keywords Wider impact assessment · Content mining · Topic model · Citation analysis · Library holdings
* Chengzhi Zhang [email protected] 1
Department of Network and New Media, Nanjing Normal University, Nanjing 210023, China
2
Department of Information Management, Nanjing University of Science and Technology, Nanjing 210094, China
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Vol.:(0123456789)
Scientometrics
Introduction Citations are commonly used to evaluate books’ impacts, which are mature in theory and feasible in operation (Kousha et al. 2011). However, citation frequency is monotonic and lacks content information, which reflects limited features of books. Meanwhile, existing research has proved that content information related to books is necessary and effective for measuring books’ impacts, such as citation contents (McCain and Salvucci 2006), book review contents (Kousha and Thelwall 2015a, 2016; Zuccala et al. 2014). Moreover, Zhou et al. (2016) revealed that multi-granularity analysis on evaluation resources can obtain more comprehensive assessment results for book impact. Therefore, multi-granularity analysis on assessment resources to integrat
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