[Purpose/significance] Researching information interaction between enterprises and users under the new media environment, and understanding user information interaction behavior characteristics, can help enterprises to understand the user needs to provide better service, so as to improve the core competitiveness of enterprises.[Method/process] By social networks and semantic analysis method, combined with the auto industry of three representative enterprises, it analyzes forwarding and forwarded, attention and focused, and reviews and commented behavior and interactive cohesion of enterprise and users information interaction with point centrality, betweenness centrality, closeness centrality and eigenvector centrality. It uses semantic keyword word frequency to analyze information interactive word frequency, and then presents the behavior characteristics of enterprises and users in the new media environment through five feature attribute indexes.[Result/conclusion] This article is based on social network analysis and semantic analysis to build the behavior model of enterprises and user information interaction under new media environment, which can be used as research framework to analyze information interaction between enterprise and user. The results of data analysis show that enterprises can use new media platforms to enhance information interaction with users and improve the competitiveness of products and services.
Wang Xiwei
,
Wei Yanan
,
Xing Yunfei
,
Wang Duo
. Research on Enterprises and Users Information Interaction Behavior Model and Characteristics in New Media Environment[J]. Library and Information Service, 2018
, 62(18)
: 6
-15
.
DOI: 10.13266/j.issn.0252-3116.2018.18.001
[1] 第40次《中国互联网络发展状况统计报告》发布[EB/OL].[2017-08-04]. http://www.cnnic.cn/gywm/xwzx/rdxw/201708/t20170804_69449.htm.
[2] 王晰巍,邢云菲,张柳,等.社交媒体环境下的网络舆情国内外发展动态及趋势研究[J].情报资料工作,2017(4):6-14.
[3] 徐升华,汤敏倩. 社会化媒体的背景、内涵与辨析——国外研究文献述评[J].情报理论与实践,2017(5):28-32,27.
[4] MARCHIONINI G. Human-information interaction research and development[J]. Library & information science research, 2008,30(3):165-174.
[5] MICHAEL J, ALBER S. Human-information interaction with complex information for decision-making[J].Informatics, 2015,2(2):4-19.
[6] ZHAO H C, SUC T, HUA Z S. To participate or not to participate in a brand micro-blog:facilitators and inhibitors[J]. Information development, 2016,32(5):1774-1785.
[7] 刘晶,李琳,李石君.基于社交网络大规模行为数据的用户关系研究[J].计算机应用与软件,2016(7):38-41.
[8] 邓胜利.网络用户信息交互行为研究模型[J].情报理论与实践,2015(12):53-56.
[9] 孙璐,李力,陶福平.信息交互能力、价值共创与竞争优势[J].研究与发展管理, 2016, 28(6):101-113.
[10] 张茫茫,傅江. 基于实体用户界面与自然用户界面结合的产品设计[J].科技导报, 2013(S2):99-102.
[11] 王晰巍,李师萌,王楠阿雪,等.新媒体环境下用户信息交互意愿影响因素与实证——以汽车新媒体为例[J].图书情报工作,2017,61(8):15-24.
[12] 侯玉.基于信息交互技术的未来功能性服装的设计[J].美与时代(上),2011(12):116-118.
[13] 马静,李衢.个人知识交互现象及管理学意义[J]. 理论与探索, 2005,28(2):132-134.
[14] 薛杨.企业微信营销中用户信息行为影响因素及作用关系研究——基于唤起和沉浸的中介作用[D].长春:吉林大学,2017.
[15] 新媒体[EB OL].[2018-01-16]. https://baike.baidu.com/item/%E6%96%B0%E5%AA%92%E4%BD%93/6206?fr=aladdin.
[16] 赵丽娟.社会网络分析的基本理论方法及其在情报学中的应用[J].图书馆学研究,2011(20):9-12.
[17] SAVIGNY H. Public opinion, political communication and the Internet[J].Politics,2002,22(1):1-8.
[18] 周慧,戴小鹏,吴丽玲,等. 基于社会网络的农民信息行为研究[J].安徽农业科学,2014(15):4904-4906.
[19] NIP J Y M, FU K W. Networked framing between source posts and their reposts:an analysis of public opinion on China's microblogs[J]. Information communication & society, 2016, 19(8):1127-1149.
[20] UDANOR C, ANEKE S, OGBUOKIRI B O. Determining social media imact on the politics of developing countries using social network analytics[J]. Program electronic library & information systems, 2016, 50(4):1-30.
[21] 王晰巍,邢云菲,赵丹,等.基于社会网络分析的移动环境下网络舆情信息传播研究——以新浪微博"雾霾"话题为例[J].图书情报工作,2015,59(4):14-22.
[22] 刘小平,田晓颖. 媒体微博的社会网络结构及其影响力分析[J].情报科学,2018(1):96-101.
[23] 许缦. 基于SICAS模型的移动APP营销模式和策略研究[J].经贸实践,2017(24):47-48.
[24] 2017中国制造业企业500强榜单发布(名单)[EB OL].[2017-09-10]. http://www.ce.cn/xwzx/gnsz/gdxw/201709/10/t20170910_25876145.shtml.
[25] ALEXA. Traffic detail[EB/OL].[2017-03-23].http://www.alexa.com/siteinfo/www.sina.com.cn.
[26] 赵康. 学术组织社群网络信息交流特征及结构演变[J].图书情报工作,2017,61(14):99-108.
[27] 蹇洁,张英培,刘雪艳,等.政务微博网络结构特征研究——以重庆市为例[J].现代情报,2017(7):55-59.
[28] 黄开木,樊振佳,卢胜军,等. 我国竞争情报领域期刊论文合著网络研究[J].情报杂志,2015(2):142-147.
[29] 谭雪晗,涂艳,马哲坤. 基于SNA的事故灾难舆情关键用户识别及治理[J].情报学报,2017(3):297-306.
[30] 任妮,周建农,戴红君. 基于文献计量的国内外信息感知与精细农业研究态势分析[J].情报探索,2017(11):104-113.
[31] 王颖. 当前接近中心性对关键研发者创造力的影响[J].情报杂志,2016(12):169-174.
[32] 武澎,王恒山. 基于特征向量中心性的社交信息超网络中重要节点的评判[J].情报理论与实践,2014(5):107-113.
