[目的/意义] 为更好地提升基于内容的引文分析效果，对国内外引用对象相关研究进行调研总结，为引用内容分析研究提供借鉴。[方法/过程] 通过调研国内外引用对象相关研究，梳理引用对象的概念定义、分类体系、应用领域和自动化识别等方面研究进展，总结当前引用对象研究不足并提出未来发展方向。[结果/结论] 引用对象从语义层面评价文献学术研究的贡献和利用价值，为引文分析方法增加了重要维度。引用对象研究需要从理论、技术和应用三个方向进行深化：理论上，加强多维度引用对象特征的研究和分析；技术上，探索基于大规模语料的自动化识别方法；应用上，尝试基于引用对象的科研评价服务。
[Purpose/significance] In order to improve the effect of content-based citation analysis, this paper summarizes the related research on citation object at home and abroad, and provides reference for citation content analysts.[Method/process] By investigating the related research on citation object at home and abroad, this paper reviewed the definitions of the citation object, classification systems, application fields and automatic identification, summarized the current research on the citation object and put forward the future development direction.[Result/conclusion] The citation object evaluates the contribution and utilization value of academic research from the semantic level, which adds an important dimension to the citation analysis method. The research on citation object needs to be deepened in three directions:theoretically, to strengthen the research and analysis of multi-dimensional citation object features; technically, to explore the automatic identification methods based on large-scale corpus; application, to try to provide scientific research evaluation services based on citation objects.
[1] DING Y, ZHANG G, CHAMBERS T, et al. Content-based citation analysis:the next generation of citation analysis[J]. Journal of the Association for Information Science and Technology, 2014,65(9):1820-1833.
[2] 赵蓉英,曾宪琴,陈必坤. 全文本引文分析——引文分析的新发展[J]. 图书情报工作, 2014, 58(9):129-135.
[3] 刘浏, 王东波. 引用内容分析研究综述[J]. 情报学报, 2017, 36(6):637-643.
[4] 胡志刚.全文引文分析[M].北京:科学出版社,2016.
[5] GARFIELD E.Can citation indexing be automated?[J].National Bureau of Standards,1964,269(114):189-192.
[6] TEUFEL S, SIDDHARTHAN A,TIDHAR D.Automatic classification of citation function[C]//Proceedings of the 2006 conference on empirical methods in natural language processing.Sydney:Association for Computational Linguistics, 2006:103-110.
[7] MUNKHDALAI T, LALOR J, YU H. Citation analysis with neural attention models[C]//Proceedings of the seventh international workshop on health text mining and information analysis (LOUHI). Austin:Association for Computational Linguistics,2016:69-77.
[8] ATHAR A,TEUFEL S.Context-enhanced citation sentiment detection[C]//Proceedings of the 2012 conference of the North American chapter of the association for computational linguistics:human language technologies.Montreal:Association for Computational Linguistics,2012:597-601.
[9] YU B,FANELLI D. Classifying negative findings in biomedical publications[J]. Association for Computational Linguistics, 2014:19-23.
[10] 许德山. 科技论文引用中的观点倾向分析[D].北京:中国科学院文献情报中心,2012.
[11] DING Y,LIUX,GUO C,et al.The distribution of references across texts:some implications for citation analysis[J].Journal of informetrics,2013,7(3):583-592.
[12] 胡志刚, 陈超美, 刘则渊,等. 从基于引文到基于引用——一种统计引文总被引次数的新方法[J]. 图书情报工作, 2013, 57(21):5-10.
[13] LIU S, CHEN C. The differences between latent topics in abstracts and citation contexts of citing paper[J]. Journal of American Society for Information Science and Technology,2013,64(3):627-639.
[14] 祝清松,冷伏海.基于引文内容分析的高被引论文主题识别研究[J].中国图书馆学报,2014,40(1):39-49.
[15] ANGROSH M A, CRANEFIELD S, STANGER N. Conditional random field based sentence context identification:enhancing citationservices for the research community[C]//Proceedings of thefirst Australasian Web conference-volume 144.Adelaide:Australian computer society,2013:59-68.
[16] SONDHI P, ZHAI C X.A constrained hidden markovmodelapproach for non-explicit citation context extraction[C]//Proceedingsof the 2014 Society for Industrial and Applied Mathematics international conference on data mining.Pennsylvania:Society for industrial and applied mathematics,2014:361-369.
[17] 雷声伟, 陈海华, 黄永,等. 学术文献引文上下文自动识别研究[J]. 图书情报工作, 2016, 60(17):78-87.
[18] ZHANG G, DING Y, MILOJEVIC S. Citation content analysis (cca):A framework for syntactic and semantic analysis of citation content[J]. Journal of the American Society for Information Science and Technology, 2013,64(7):1490-1503.
[19] 陆伟,孟睿,刘兴帮. 面向引用关系的引文内容标注框架研究[J]. 中国图书馆学报, 2014,40(6):93-104.
[20] SMALL H. Cited documents as concept symbols[J]. Social studies of science, 1978, 8(3):327-340.
[21] RITCHIE A, TEUFEL S, ROBERTSON S. How to find better index terms through citations[C]//Proceedings of COLING/ACLworkshop on how can computational linguisticsimproveinformation retrieval.Sydney:Association for Computational Linguistics,2006:25-32.
[22] QAZVINIAN V,RADEV D R. Scientific paper summarization using citation summary networks[C]//Proceedings of the 22nd international conference on computational linguistics.Manchester:Association for Computational Linguistics,2008:689-696.
[23] QAZVINIAN V,RADEV D R,OZGUR A. Citation summarization through keyphraseextraction[C]//Proceedings of the 23rd international conference on computational linguistics.Beijing:Association for Computational Linguistics,2010:895-903.
[24] ANDERSON M H, SUN Y T. What have scholars retrieved from Walsh and Ungson (1991)? a citation context study[J].Management learning,2010,41(2):131-45.
[25] JHA R,ABU-JBARA A, RADEV D.A system for summarizing scientific topics starting from keywords[C]//Proceedings of the 51st annual meeting of the Association for Computational Linguistics.Sofia:Association for Computational Linguistics, 2013:572-577.
[26] KHALID A, KHANAF A, IMRANB M,et al.Reference terms identification of cited articles as topics from citation contexts[J].Computers and electrical engineering,2018,20(3):1-12.
[27] GARZONE M, MERCER R E. Towards an automated citation classifier[C]//Advances in artificial intelligence. Berlin:Lecturenotes in computer science, 2000:337-346.
[28] RADOULOV R. Exploring automatic citation classification[D].Waterloo:University of Waterloo,2008.
[29] RADEV D R, MUTHUKRISHNAN P, QAZVINIAN V, et al. The ACL anthology network corpus[J]. Language resources andevaluation,2013,47(4):1-26.
[30] BIKEL D M, MILLER S, SCHWARTZ R, et al. 1997. Nymble:a high-performance learning name-finder[C]//Proceedings of the fifth conference on applied natural language processing.Washington:Association for Computational Linguistics,1997:194-201.
[31] LAFFERTY J D, MCCALLUM A, PEREIRA F C N. Conditional random fields:probabilistic models for segmenting and labeling sequence data[C]//Eighteenth international conference on machine learning.Williamsport:Morgan Kaufmann Publishers Inc, 2001:282-289.
[32] MA X,HOVY E. End-to-end sequence labeling via bi-directional LSTM-CNNs-CRF[C]//Proceedings of the 54th annual meeting of the association for computational linguistics.Berlin:Association for Computational Linguistics, 2016:1064-1074.
[33] DEVLIN J,CHANG M W, LEEK,etal.BERT:Pre-training of deep bidirectional transformers for language understanding[EB/OL].[2018-12-13]. https://arxiv.org/abs/1810.04805.
[34] PETERS M E, AMMAR W, BHAGAVATULA C, et al. Semi-supervised sequence tagging with bidirectional language models[C]//Proceedings of the 55th annual meeting of the Association for Computational Linguistics. Vancouver:Association for Computational Linguistics,2017:1756-1765.
[35] YANGZ L, SALAKHUTDINOV R, COHEN W W. Transfer learning for sequence tagging with hierarchical recurrent networks[C]//Proceedings of the 5th international conference on learning representations.Toulon:The DBLP Computer Science Bibliography,2017.
