Infgraph: Influential Researcher and Cited Research Analysis Using Citation Network

Infgraph: Influential Researcher and Cited Research Analysis Using Citation Network

M. Geetha. (4c5df6a5-2de1-4fe2-931e-2244dd9617aa, K. Suresh Kumar (5a673c34-1198-4f66-bcca-a6ed0f148b21, Ch. Vidyadhari (156ea7f4-c4a4-4b02-b555-4168eea8b781, R. Ganeshan (64a4b47c-93f1-4916-94eb-736ce70b1e60
Copyright: © 2022 |Pages: 19
DOI: 10.4018/IJDSST.311065
Article PDF Download
Open access articles are freely available for download

Abstract

The understanding of references in research articles is essential for performing effectual research. This paper devises a hybrid model to find the influential cited paper and influential researchers from Web of Science (WOS) data. For determining the influential researcher, a series of steps is performed. Then the co-citation is performed for providing author-author co-relation that predicts the next co-author. Thereafter, visualization of the network is performed for research communication amongst different authors. Then, the network density is computed. Finally, the cluster coefficient is adapted for finding the influential researcher. Concurrently, for discovering influential cited papers, the pre-processing is performed using the stop word removal and stemming process. Then, the word2vec model is utilized for training the model to forecast the suitable word that comes next. Finally, the modified word mover's distance (MWMD) is utilized for determining the semantic similarity in order to discover influential cited papers.
Article Preview
Top

1. Introduction

Citation analysis is a useful technique in the assessment of the impact of an article and discovers the significant articles in a certain field. Also, it has become an integral part of the decision making procedure in scientific and academic life as a foundation for ranking institutions, journals, authors, and even for creating promotion decisions. The speediness and development scope in these areas made it crucial for the researchers to be conscious of data published across various research domains and various organizations (Kajikawa & Takeda, 2009). The citation network of the paper helps to depict the cited relation amongst various papers (Thakur, 2018; Thakur, 2017) which has offered a promising way for modeling the correlation amongst the papers (Liu, et al., 2019). In social networks, the actors connect with the interactions for exchanging valued resources. The citation network is an explicit social network wherein the actors indicate articles, journals, and authors. In this method, the valued resources indicate knowledge and ideas and the interactions represent the citation of actors (Pieters, et al., 1999).

The assessment of scholarly communication by citation patterns is widely utilized for determining the scientific teamwork that mapped scholarly disciplines and assessed the influence of investigation outcomes and scrutinized knowledge transport amongst several areas. The citations are utilized for establishing a network that involves author citation networks in which the node indicates papers, journals, and authors and the edge signifies the count of papers that are cited, and co-cited. Even though the easy count of citation remained an imperative indicator, but it's limited to semantics (Ding, et al., 2014). The impact factor of scientific publications is evaluated by considering the count of citations they receive. It depicts how regularly they are being referenced by other publications. This publication has linked authors that originate institutions and venues of publication that involves conference, journals, and proceedings for comparing the scientific impact. For example, one frequently adapted indicator is the impact factor which helps to determine the journal quality. The impact factor is yearly published using Journal Citation Report (JCR) by adapting citations (Rahm & Thor, 2005). The adaption of citation analysis is to provide an evaluation of research, which aimed to evaluate the altered scholarly work contribution considering knowledge advancements. The scientists help to cite the work as they discover it to be most beneficial for perusing the research. The count of citations received by the publication is considered a quantitative measure of resonance and has built a scientific community (Neuhaus & Daniel, 2008).

Complete Article List

Search this Journal:
Reset
Volume 16: 1 Issue (2024)
Volume 15: 2 Issues (2023)
Volume 14: 4 Issues (2022): 1 Released, 3 Forthcoming
Volume 13: 4 Issues (2021)
Volume 12: 4 Issues (2020)
Volume 11: 4 Issues (2019)
Volume 10: 4 Issues (2018)
Volume 9: 4 Issues (2017)
Volume 8: 4 Issues (2016)
Volume 7: 4 Issues (2015)
Volume 6: 4 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing