A large number of theoretical and empirical studies on citation behavior have been conducted internationally. Although some theoretical studies on such topic have been carried out in China, few studies have focused sp...A large number of theoretical and empirical studies on citation behavior have been conducted internationally. Although some theoretical studies on such topic have been carried out in China, few studies have focused specifically on this area from an empirical perspective, resulting in the lack of literature on the findings of actual surveys. To address this challenge, we conducted two questionnaire surveys to understand the motivations of the researchers on citation. One survey covers the authors who published articles in Chinese Journal of Scientific and Technical Periodicals, while the other targets the most productive and most cited Chinese authors in library and information science. The results show that citation behavior is not only motivated by rational factors, but also by other social factors.展开更多
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...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.展开更多
基金supported by National Natural Science Foundation of China(Grant No.70673019)
文摘A large number of theoretical and empirical studies on citation behavior have been conducted internationally. Although some theoretical studies on such topic have been carried out in China, few studies have focused specifically on this area from an empirical perspective, resulting in the lack of literature on the findings of actual surveys. To address this challenge, we conducted two questionnaire surveys to understand the motivations of the researchers on citation. One survey covers the authors who published articles in Chinese Journal of Scientific and Technical Periodicals, while the other targets the most productive and most cited Chinese authors in library and information science. The results show that citation behavior is not only motivated by rational factors, but also by other social factors.
文摘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.
