Analysis on cited times of papers published in Neural Regeneration Research

Introduction Publication Name=Neural Regeneration Research （NRR） Timespan=2008-2011. Databases=SCI-EXPANDED, SSCI, A＆HCI, CPCI-S, CPCI-SSH. Web of Science Categories： CELL BIOLOGY （938）, NEUROSCIENCE （938） Document Types： ARTICLE （922）, REVIEW （13）, EDITORIAL MATERIAL （2）, LETTER （1） Search time： 23/06/2011 A total of 938 articles published till the search time in NRR are searched, including 315 papers published in 2008, 185 in 2009, 321 in 2010, and 117 in 2011. Totally 111 papers have been cited and the total number of citations is 171. There are 76 self-citations, and 95 non-self citations, which are scattered in 85 journals. The citation situations are listed as follows.

Paper Analysis of Shanghai Ocean University in Bibliometric Method from Web of Science

The data of this research was mainly collected from the Web of Science (WOS) and Incites database platform, which was filtered and cataloged according to the different platforms. For tracing the change in scientific research at Shanghai Ocean University, make use of Bibliometric analysis to get the image and table of highly cited papers and hot papers. In this study, the scientific aspects in highly cited papers and hot papers, published in the last year in the core collection of Web of Science, were taken as objects, and office software was used as the main tool to carry out bibliometric and figure analysis. From the four aspects to find the difference in these fields, the production of specific fields and cited times is inconsistent. And suggest the department and management adjust the policy and method via elastic personnel and rewards to prompt the advancement of the research fields.

CiteOpinion: Evidence-based Evaluation Tool for Academic Contributions of Research Papers Based on Citing Sentences

Purpose:To uncover the evaluation information on the academic contribution of research papers cited by peers based on the content cited by citing papers,and to provide an evidencebased tool for evaluating the academic value of cited papers.Design/methodology/approach:CiteOpinion uses a deep learning model to automatically extract citing sentences from representative citing papers;it starts with an analysis on the citing sentences,then it identifies major academic contribution points of the cited paper,positive/negative evaluations from citing authors and the changes in the subjects of subsequent citing authors by means of Recognizing Categories of Moves(problems,methods,conclusions,etc.),and sentiment analysis and topic clustering.Findings:Citing sentences in a citing paper contain substantial evidences useful for academic evaluation.They can also be used to objectively and authentically reveal the nature and degree of contribution of the cited paper reflected by citation,beyond simple citation statistics.Practical implications:The evidence-based evaluation tool CiteOpinion can provide an objective and in-depth academic value evaluation basis for the representative papers of scientific researchers,research teams,and institutions.Originality/value:No other similar practical tool is found in papers retrieved.Research limitations:There are difficulties in acquiring full text of citing papers.There is a need to refine the calculation based on the sentiment scores of citing sentences.Currently,the tool is only used for academic contribution evaluation,while its value in policy studies,technical application,and promotion of science is not yet tested.

2016 Highly Cited Paper Award and Best Reviewer Award of Petroleum Science

Petrolezum Science is pleased to announce the winners of the 2016 Highly Cited Paper Award in which we recognize highly cited papers published in our journal between 2014and 2015.Citation data of papers are based on citations in Web of Science in 2016.Petroleum Science also announces the winners of the 2016 Best Reviewer Award who have made an outstanding contribution in 2016 as reviewer to Petroleum Science.Congratulations and thanks to all the winners!The winners of the 2016 Highly Cited Paper Award

Research on the structural features and influencing factors of the scientific exchange network of countries along "the belt and road"

"The Belt and Road" is an initiative proposed by China in recent years to cooperate and develop to build a community with a shared future for mankind. Analyzing the academic exchanges of countries along the "The Belt and Road" can provide a quantitative reference for future international scientific and technological exchanges, collaborative innovation development and related research. We carry out matrix construction and network structure analysis on the citation and cooperation of highly cited papers among countries along the "Belt and Road" included in China from 2013 to 2018 included in Web of Science Core Collection, and explore the current status of scientific exchanges in countries along "the Belt and Road". The Quadratic Assignment Procedure analysis method verifies the influence of five variables, including geographic proximity, differences in economic levels, scientific productivity, similarity of research content,and economic and trade cooperation, on scientific exchange networks. The research results show that the countries along the "the Belt and Road" have relatively close academic exchanges;Geographical proximity, similarity of research content, differences in economic level between countries, and differences in scientific productivity are significantly correlated with each other;the similarity of scientific and technological level and research content and the closeness of economic and trade cooperation have a positive effect on scientific exchanges as a whole.