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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (9): 50-58    DOI: 10.11925/infotech.2096-3467.2018.0157
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Growth Pattern of Online News Comments
Zong Hong, Xue Chunxiang(), Chen Fen
School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
Jiangsu Collaborative Innovation Center of Social Safety Science and Technology, Nanjing 210094, China
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Abstract  

[Objective] This study tries to identify the growth law of online news comments, aiming to explore their aging rules and potential values. [Methods] We proposed the growth measurement index of online news comments, including their growth cycle, growth peak, absolute concentration value, peak concentration index, and growth half-life. Then, we used online news and comments from sina.com to conduct an empirical study. [Results] We found that most online news comments had short growth cycles, low growth peaks, and earlier positions of peak concentrations. There were four leading growth patterns, including negative exponential, flat, uni-modal and multi-band. The growth of online news comments is affected by the aging of news, the time of news release, as well as the occurrence of relevant or the follow-up events. [Limitations] The sample data was from one website. [Conclusions] This paper analyzes the growth law of online news comments and identifies four types of growth patterns.

Key wordsOnline News Comments      User Comments      Information Obsolescence      Growth Pattern     
Received: 06 February 2018      Published: 25 October 2018
ZTFLH:  分类号: G203 G206  

Cite this article:

Zong Hong,Xue Chunxiang,Chen Fen. Growth Pattern of Online News Comments. Data Analysis and Knowledge Discovery, 2018, 2(9): 50-58.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.0157     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I9/50

研究者 研究对象 阶段划分情况
易臣何(2014)[15] 突发事件网络舆情 生成、扩散、消减
梁芷铭(2014) [16] 微博热点话题 成长、成熟、衰退
姜祎, 等(2014) [17] 网络信息 价值形成、价值激活、价值实现、价值消亡
Chen, 等(2003) [18] 新闻事件 产生、增长、衰退、消亡
曾艺林(2014) [19] 涉官网络谣言 萌发、扩散、变化、余热
王旭, 等(2017) [20] 突发事件网络舆情 萌芽期、成长期、成熟期、衰退期
武超群(2016) [21] 公共危机网络舆情 酝酿期、生成期、扩散期、消解期、沉寂期
新闻类别 新闻总数(篇) 有效样本数量
新闻(篇) 评论(条)
财经 1 031 385 7 335
时尚 12 9 358
军事 17 15 1 189
健康 2 0 0
社会 566 293 9 276
育儿 6 1 3
司法 43 24 661
科技 489 137 3 018
收藏 2 1 1
女性 20 9 242
教育 29 15 62
娱乐 129 96 12 643
国际 43 32 2 155
国内 315 175 14 832
总计 3 037 1 192 51 775
新闻类别 数据量(条) 最小值(分钟) 最大值(分钟) 均值
(分钟)
标准差
(分钟)
财经 385 0 250 401 903.51 12 829.17
社会 293 0 49 865 389.31 2 925.70
科技 137 0 37 415 472.88 3 311.08
娱乐 96 0 20 895 1 012.21 2 948.11
国际 32 0 1 875 549.19 415.59
国内 175 0 27 235 510.15 2 432.59
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