Showing 2 results for Atapour
Hashem Atapour, Fatima Fahimnia,
Volume 5, Issue 1 (6-2018)
Abstract
Background and Aim: this research investigates the impact of authors’ rank in Bibliographic networks on document-centered model of Expertise Retrieval. Its purpose is to find out what kind of authors’ ranking in bibliographic networks can improve the performance of document-centered model.
Methodology: Current research is an experimental one. To operationalize research goals, a new test collection was developed which includes 55 queries and 96375 documents. The queries were made by Iran Knowledge and Information Science PhD students, and the documents were papers indexed in the Web of Science database under Library Science and Information Science category. The queries were submitted to the database consisting of test collection documents, and then DLH13, a known IR model, were used to retrieve documents from database. The first 100 documents retrieved by DLH13 model for each query were chosen for second stage. All people names occurred in the retrieved documents were extracted, processed, and ranked in 5 different ways based on micro metrics of Social Network Analysis. The top 10 results of every method accumulated in a pool of authors. After relevance judgment on authors’ expertise, the expert finding performance of every ranking method was measured.
Findings: Results showed that performance of authors’ ranking in citation networks hadn’t significant difference with document-centered model, whereas authors’ ranking in co-authorship networks was weaker than document-centered model, and impact it negatively.
Conclusion: compared with author-based networks, citation-based networks are better evidence for individual’s expertise in different subject areas.
Dr Hashem Atapour, Ms Zahra Shiravand, Dr Rasoul Zavaraqi,
Volume 5, Issue 4 (3-2019)
Abstract
Background and Aim: The last two decades have witnessed efforts to identify ways and tools of showing the value of science for society known as the social impact of science, the efforts that have been made under various titles such as social benefits, social quality, social utility, social relevance, and so on. Academic publications, especially academic articles, are objective representation of scientific activities. One question raised in this regard is which kind of academic articles can have much more social impact. Bornmann (2014) argues articles that review previous studies and provide evaluative reports are of greater potential for social impact. Accordingly, the purpose of this research is to compare the social impact of review articles with the original research articles indexed in the Web of science in four fields including psychology, pharmacy, biology, and agriculture.
Methods: Current research is an applied one and has applied altmetrics analysis. Research and review articles were retrieved from Web of Science database, and altmetric score of articles is collected using Bookmarklet tool of Altemetric.com. The population of this research is composed of review and research articles of abovementioned fields indexed in the Web of Science in 2015. Using a randomized stratified sampling method, a sample of the research population has been chosen for more investigation. SPSS software was used to analyze the data.
Results: The findings of this research shows that there is a significant difference between the altmetric score of review and research articles, in a way that the altmetric score of review articles is higher than research articles. Both review and research articles have been mentioned in Mendeley more than the other social media, but these articles have received the least mention from the Wikipedia.
Conclusion: It is concluded that review articles have more social impact than research articles. The fact that strengthens the position of review articles in the body of scientific publications more than before.
