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大数据热的冷思考 被引量:9

Rethinking the Popularity of Big Data
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摘要 在互联网技术高速发展的今天,大数据重构传媒行业,是产业当下的热点话题。毫无疑问,大数据将给传媒业带来巨大的经济效益。然而,大数据的发展过程也存在着种种问题和隐患,需要传媒业对它的价值进行重新评估。本文通过分析大数据研究方法的缺陷、用户隐私安全问题以及引起的社会担忧三个方面,对目前传媒业中的大数据热进行冷思考,以为政府、学界、业界对大数据的应用实践提供借鉴。 With a rapid development of intemet technology, big data has reconstructed media industry, which is one of the hottest topics in the industry nowadays. And big data is bringing media industry substantial economic benefits. However, big data is not omnipotent. It's struggling with some problems potentially causing some damages to our life, which require scholars and professionals in media industry to rethink its influence and value profoundly. This essay analyzes the downsides of big data research method, user privacy and security issues as well as the social worries it has caused. By analyzing the influence of big data's hot trend rationally, this essay has provided references for the practices of government, academia and the industry.
作者 匡文波 黄琦翔 KUANG Wenbo HUANG Qixiang
出处 《国际新闻界》 CSSCI 北大核心 2016年第8期134-148,共15页 Chinese Journal of Journalism & Communication
基金 国家社会科学基金项目<新媒体在"茉莉花革命"中的作用机理研究>(立项批准号:11BXW037)的研究成果~~
关键词 大数据 冷思考 隐私安全 机器人新闻 社会歧视 big data, cold thinking, privacy security, robot news writing, social discrimination
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  • 1蒋均牧(2012).《互联网一天信息量等于1.68亿张DVD》.检索于http://www.edu.cn/sj_6538/20121112/t20121112_867987.shtml.
  • 2Jiang, Junmu (2012).The daily amount of information equals 168,000,000 DVD. Retrievedfromhttp://www.edu.cn/sj_6538/20121112/t20121112_867987.shtml.
  • 3亚马逊中国(2015).《全民阅读调查报告发布浅阅读成趋势》.检索于http://oversea.huanqiu.com/article/2015-04/6255073.html.
  • 4AmazonChina (2015).TAe Whole Chinese People Reading Investigation Report Release:Shallow Reading is Becoming Tre/jd Retrieved fromhttp://oversea.huanqiu.com/article/2015-04/6255073.html.
  • 5Butler, Declan (2013).When Google got flu wrong. Retrieved from http://www.nature.com/news/when-google-got-flu-wrong-1.12413.
  • 6Lazer, D., Kennedy, R., King,G. & Vespignani, A. (2014).Big data. The parable of Google flu: traps inbig data analysis. Scinece,343 (6176),1203-1205.
  • 7Marcus, Gary & Davis, Ernest Q.0\6)Problems With Big Data. Retrieved from http://www.nytimes.com/2014/04/07/opinion/eight-no-nine-problems-with-big-data.html?_r=0.

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