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Journal of library and information science in agriculture ›› 2020, Vol. 32 ›› Issue (3): 37-43.doi: 10.13998/j.cnki.issn1002-1248.2019.11.20-1004

• Research paper • Previous Articles     Next Articles

The Cross-integration Development Path of Information Science and Communication Science in the Background of Artificial Intelligence and Big Data

MA Xiaoyue1, XUE Pengzhen2   

  1. 1. School of Journalism and New Media, Xi'an Jiaotong University, Xi'an 710049;
    2. School of Economics and Management, Xidian University, Xi'an 710071
  • Received:2019-11-18 Online:2020-03-05 Published:2020-03-23

Abstract: [Purpose/Significance] Clarify the research status of cross-integration research of information science and communication under the background of artificial intelligence and big data, and explore new research directions of collaborative development. [Method/Process] Through the systematic sorting, summarization and analysis of the cross-related literature of the disciplines of information science and communication, the paper analyzes the cross-research topics of theoretical research and practical application, as well as their respective research characteristics and focuses. Combined with artificial intelligence, big data research methods and research hotpots, the new research directions and future development trends in the intersection process of information science and communication are expounded. [Results/Conclusions] In the context of artificial intelligence and big data, the intersection of information science and communication science is mainly based on information and society, which is reflected in the intersection of research objects, the intersection of research methods, and the intersection of application fields. In the future, the cross-research direction will further penetrate each other through the continuous development of data science. At the same time, the two disciplines will complement each other at the meso level, and use the information forecasting, multi-source data fusion and fusion media to achieve comprehensive collaborative development.

Key words: artificial intelligence, big data, intelligence science, communication science, cross-collaboration

CLC Number: 

  • G354.2
[1] Karunan K, Lathabai H H, Prabhakaran T.Discovering interdisciplinary interactions between two research fields using citation networks[J]. Scientometrics,2017,113(1):335-367.
[2] 许海云,尹春晓, 郭婷,等.学科交叉研究综述[J].图书情报工作,2015,59(5):119-127.
[3] 闵超,孙建军.学科交叉研究热点聚类分析——以国内图书情报学和新闻传播学为例[J]. 图书情报工作,2014,(1):109-116.
[4] 王昊. 基于关联规则挖掘研究学科间相关性[J].现代图书情报技术,2005,(03):23-28.
[5] Hu J, Zhang Y.Discovering the interdisciplinary nature of Big Data research through social network analysis and visualization[M]. Springer-Verlag New York, Inc.2017.
[6] [美]J·H·谢拉著,张沙丽译.图书馆学引论[M].兰州:兰州大学出版社,1956.
[7] 张锦.图书情报学引进传播学理论述评[J].图书与情报,1999,(2).
[8] 黄纯元. 传播学和情报学[J].情报学刊,1983,(4):21-23.
[9] 刘超,李秀霞,邵作运.国内图书情报学与新闻传播学间学科影响度和交叉度分析——基于期刊引文分析[J].情报杂志,2017,(07):99+115-119.
[10] 王传清,连鸿江.图书情报学与传播学理论交叉研究综述[J].图书情报工作,2004,48(8):94-97.
[11] 王亚军. 用传播学效果分析原理指导阅读辅导的策略与方式[J]. 情报杂志,2001,20(11):63-64.
[12] 马费成. 推进大数据、人工智能等信息技术与人文社会科学研究深度融合[J].评价与管理,2018,16(02):3-7.
[13] 马费成,张瑞,李志元.大数据对情报学研究的影响[J].图书情报知识,2018,(05):4-9.
[14] 王知津. 大数据时代情报学和情报工作的“变”与“不变”[J].情报理论与实践,2019,42(07):1-10.
[15] [美]Stephen W,Littlejohn.人类传播理论[M].北京:清华大学出版社.2009.
[16] 曾凡斌,陈荷.基于谷歌图书语料库大数据的百年传播学发展研究[J]. 现代传播:中国传媒大学学报,2018.
[17] 马秀峰,张莉,李秀霞.我国图书情报学与新闻传播学间的学科知识交流与融合分析[J].情报杂志,2017(02):63-69.
[18] 郭晓真. 人工智能时代传播学的现状与反思探究[J].传播力研究,2018,2(27):7-9.
[19] Reis F, Maricato JD.Scientific production of researchers linked to faculties of communication and information science and interdisciplinary relations between the fields[J].Informacao &Sociedade-Estudos,2018,28(2):227-244.
[20] 邢晓光. 大数据背景下传播学研究方式的转变[J].科技风,2018,(31):62.
[21] 郝龙,李凤翔.社会科学大数据计算——大数据时代计算社会科学的核心议题[J].图书馆学研究, 2017,(22):22-31+37.
[22] Younghee Noh.Imagining Library 4.0: Creating a Model for Future Libraries[J].The Journal of Academic Librarianship,2015,(41):786-797.
[23] Khan S A, Bhatti R.Digital competencies for developing and managing digital libraries[J].The Electronic Library, 2017,35(3):573-597. [24] 李广建,杨林.大数据视角下的情报研究与情报研究技术[J].图书与情报,2012,(6):1-8.
[25] 化柏林. 多源信息融合方法研究[J].情报理论与实践,2013,36(11):16-19.
[26] 苏玲,娄策群.我国情报学和传播学领域大数据研究探析[J].情报科学,2019,37(05):31-37.
[27] 王连喜,曹树金.学科交叉视角下的网络舆情研究主题比较分析——以国内图书情报学和新闻传播学为例[J].情报学报,2017,(02):53-63.
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