ebrahim Emami Gharetappeh; Farideh Osareh; saeedeh Ebrahimy
Abstract
Since scientometrics has changed significantly over time, study of its changes can include a description of the past, an analysis of the current situation, and planning for the Future, leading to optimal policymaking and planning by organizations. The objective of the present study was to identify trends ...
Read More
Since scientometrics has changed significantly over time, study of its changes can include a description of the past, an analysis of the current situation, and planning for the Future, leading to optimal policymaking and planning by organizations. The objective of the present study was to identify trends and driving forces affecting future research in the field of scientometrics in Iran based on the characteristics of the knowledge-based society. This study is applied that has conducted by literature review and survey. An expert panel was conducted with 15 experts in the field of Knowledge Science. Then, a researcher-made questionnaire was distributed among the experts. The study results showed that the driving forces affecting the Future of scientometrics can be divided into 14 general indicators (10 internal indicators including communication and interactions, experts, creativity and innovation, information technology, citation, methodology, index, language barriers, facilities, and specific problems of the field and 4 external indicators including sociology, economics, information technology and policymaking and management of the country's higher education system) with 66 items. Given the undesired situation of trends of scientometrics in Iran, policymakers and managers of the country's higher education system in Iran should consider the need to change the trends and the effective drivers of scientometrics because the lack of synchronization with the changes, the effectiveness, and applicability of research will reduce and faded over time.
Saeideh Ebrahimy; Fatemeh Setareh
Volume 16, Issue 2 , July 2018
Abstract
This study aimed to assess the paths through which save metrics (on CiteULike, Mendeley, and Figshare) and discussion metrics (on Twitter, Facebook, and Wikipedia) influence citation. This descriptive-correlation study investigates the relationships between different variables based on its proposed conceptual ...
Read More
This study aimed to assess the paths through which save metrics (on CiteULike, Mendeley, and Figshare) and discussion metrics (on Twitter, Facebook, and Wikipedia) influence citation. This descriptive-correlation study investigates the relationships between different variables based on its proposed conceptual model. Systematic and stratified sampling was employed and, using the Cochrane formula, the sample size was determined to be 1892 articles. Data were collected using the PLOS altmetrics, and path analysis was administered to test the conceptual model by using AMOS software. The results convey that Mendeley was the most effective path resulting to citation. Mendeley has a positive and significant relationship with citation via save as an intermediator. Twitter also had a negative and significant relationship with citation via discussion as an intermediating factor. Yet, neither save metrics on CiteULike and Figshare nor discussion on Facebook and Wikipedia does create a path of influence on citation. Identifying the effective paths through which social networks affect citation via altmetrics and presenting a final model of those paths could enrich and expand the theoretical foundations in the field of altmetrics. Besides identifying the most effective social networks and paths for online scientific interactions that lead to citation, the implications of this research can provide deeper insights for policy makers, editors and scholars.
Saeideh Ebrahimi; Fatemeh Setareh
Volume 15, Issue 2 , June 2017
Abstract
A review on previous literature shows that there is a correlation between discussion and recommendation. Therefore, we aimed to assess the relationship between these two metrics in four systems (Scopus, Web of Science, PubMed Central, and CrossRef) simultaneously and separately. This was a descriptive ...
Read More
A review on previous literature shows that there is a correlation between discussion and recommendation. Therefore, we aimed to assess the relationship between these two metrics in four systems (Scopus, Web of Science, PubMed Central, and CrossRef) simultaneously and separately. This was a descriptive correlational study on 90728 research articles published in seven biomedical journals in the PLOS system during 2009-2013. The sample size was calculated based on the Cochrane formula to be 1892 articles. For data collection, PLOS system was used which enables free access to the articles of important biomedical journals. This system includes 7 journals cited from 2003. Data were analyzed usingSPSSsoftware, version21. Inthis study, we found a negative and statistically significant correlation between discussion on Twitter and the citation-based systems. We found no correlation between discussion on Facebook and citation. On the other hand, we found a positive and statistically significant correlation between recommendation by F1000 and citation. We found that discussion on virtual networks and recommendation are two types of feedback in virtual environments. However, among the various systems, the F1000 and Wikipedia were able to provide significant feedback leading to citation.
saeideh Ebrahimy; Farideh Osareh
Volume 14, Issue 2 , July 2016
Abstract
It has seen in many studies that there is a significant relation between the number of authors in an article and its amount of perceived citations. In other words, the more the number of the authors, the more the possibility of perceiving citations. The present study thus is going to explain a kind of ...
Read More
It has seen in many studies that there is a significant relation between the number of authors in an article and its amount of perceived citations. In other words, the more the number of the authors, the more the possibility of perceiving citations. The present study thus is going to explain a kind of behavior, which is based on Citing Conformity factor. The research has been done in two parts: 1. Survey Method 2. Citation analysis method. The findings obtained from regression analysis test suggest that according to Informational Citing Conformity factor, 26% of changes in this type of behavior are predictable. It means, having a motivation for healthy thoughts and honesty and also selecting more credible source of information, the authors resort to cite the articles which were written by more authors. The results also indicated that Normative Citing Conformity is not a suitable predictor for this kind of motivation. The relationship between Citing Conformity Factors (Normative, Informational) and the motivation to cite multi author articles has been analyzed in this research for the first time.
S. Ebrahimy; F. Osareh
Volume 10, Issue 2 , July 2012, , Pages 1-13
Abstract
This study historically analyzes the scientific output of Mathematics to describe its structure, notions and scientific origin using the historiographical method. The research data consisted of scientific outputs of Mathematics in ISI database, Science Citation Index (SCI) and Social Science Citation ...
Read More
This study historically analyzes the scientific output of Mathematics to describe its structure, notions and scientific origin using the historiographical method. The research data consisted of scientific outputs of Mathematics in ISI database, Science Citation Index (SCI) and Social Science Citation Index (SSCI) during 8 years (1990 to 2007). The data collection tool was the search engine and the analysis part of the WOS and also HistCiteTM software. According to White (2003), the sample of the study was circa one percent of the studied data (i.e. 120 documents) that was analyzed based on two different aspects: Local Citation Score (LCS) and Global Citation Score (GCS).The research results show that with regard to Local Citation Score (LCS), five scientific clusters were formed and all of them were related to different fields of “Mathematics Education”. Based on Global Citation Score (GCS), there were no significant scientific cluster in this field, and this is while the amount of Global Citation Score was significantly more than Local Citation Score. According to the findings it seems that: 1. The major scientific clusters and transitions in Mathematics are mostly related to theoretical fields as this issue has caused a new paradigm in this discipline. 2. The amount of this scientific field’s influence on Applied Mathematics is much more than the non- Applied Mathematics.
