搜索

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

在线热点事件的时空演变规律

龚凯 唐明 尚明生 周涛

引用本文:
Citation:

在线热点事件的时空演变规律

龚凯, 唐明, 尚明生, 周涛

Empirical study on spatiotemporal evolution of online public opinion

Gong Kai, Tang Ming, Shang Ming-Sheng, Zhou Tao
PDF
导出引用
  • 为了理解舆论的时空演变斑图并揭示其形成机理, 本文运用统计物理学方法, 通过对在线评论数据进行统计分析, 定量地研究了在线热点事件关注度(在线评论数) 的时空演变规律. 实证表明, 虽然事件关注度在不同地区的分布存在极大的异质性, 即遵循双段幂律分布; 但是不同地区内事件的关注程度在时间演变过程中却表现出明显的一致性, 其不同时间内的Zipf分布变化很小. 关联性分析显示地区关注度受到该地区经济的显著影响, 而不同地区关注度演变行为的一致性来源于地区之间的强关联性. 另一方面, 舆论引导将显著影响事件的关注度, 导致传播速度(单位时间内评论数的增量) 急剧增加. 通过计算不同地区传播速度的信息熵, 我们发现评论的地区分布在大部分时间内都具有一致性, 而舆论引导有助于保持这种一致性. 地区传播速度之间的关联性分析表明在整个事件中经济较发达地区的舆论变化更趋于一致, 暗示这些地区对于舆论引导的响应更快, 因此加强发达地区的舆论引导有利于控制舆论的整体传播.
    To understand the spatiotemporal evolution of online public opinion and reveal its formation mechanism, we investigate the data from several popular online comments by means of statistical physics. Although the empirical results show that the heterogeneity of concerns exists in different areas, which follows a double power law, an obvious consistency of such concerns occurs during the evolution of online public opinion. Through correlation analysis, we reveal that the regional population and economy may have a significant influence on the concern about the event, and find that the consistency of concerns in different areas derives from the strong correlations among regions. On the other hand, the public opinion guide can significantly affect the concern about the event, and lead to the rapid increase of propagation velocity. By calculating the information entropy of propagation velocity, we find that the geographical distribution of online comments is relatively stable in most time, and the public opinion guide may help to maintain this consistency. Furthermore, the correlation analysis shows that the more developed areas tend to be more synchronized, which suggests the responses of these areas to the public opinion guide may be faster. Therefore, enhancing the guide of public opinion in developed areas can help our government to control the spread of the online public opinion.
    • 基金项目: 国家自然科学基金重大研究计划(批准号: 90924011, 91024026)和国家自然科学基金青年科学基金(批准号: 11105025)和资助的课题.
    • Funds: Project supported by the Major Research Plan of the National Natural Science Foundation of China(Grant Nos. 90924011, 91024026), and the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 11105025).
    [1]

    Castellano C, Fortunato S, Loreto V 2009 Rev. Mod. Phys. 81 591

    [2]

    Zhou T,Wang B H, Han X P, Shang M S 2010 Jour. Syst. Eng. 25 742 (in Chinese)[周涛, 汪秉宏, 韩筱璞, 尚明生2010系统工程学报25 742]

    [3]

    Moreno Y, Nekovee M, Pacheco A F 2004 Phys. Rev. E 69 066130

    [4]

    Eubank S, Guclu H, Kumar V S A, Marthe M V, Srinivasan A, Toroczkai Z,Wang N 2004 Nature 429 180

    [5]

    Liu J Z, Wu J S, Yang Z R 2004 Physica A 341 273

    [6]

    Zheng D F, Hui PM, Trimper S, Zheng B 2005 Physica A 352 659

    [7]

    Sznajd W K, Sznajd J 2000 Int. J. Mod. Phys. C 11 1157

    [8]

    Deffuant G, Neau D, Amblard F, Weisbuch G 2000 Adv. Compl. Sys. 3 87

    [9]

    Galam S 2008 Int. J. Mod. Phys. C 19 409

    [10]

    H Kesten, V Sidoravicius 2005 Annals Prob 33 2402

    [11]

    Zhou J, Liu Z H, Li B 2007 Phys. Lett. A 368 458

    [12]

    Pan Z F, Wang X F, Li X 2006 Jornal of System Simulation 18 2346 (in Chinese)[潘灶烽, 汪小帆, 李翔2006系统仿真学报18 2346]

    [13]

    He M H, Zhang D M, Wang H Y, Li X G 2010 Acta Phys. Sin. 59 5175 (in Chinese)[何敏华, 张端明, 王海艳, 李小刚, 方频捷2010 59 5175]

    [14]

    Zhang L, Liu Y 2008 Journal of Beijing Jiaotong University. 2 67 (in Chinese)[张力, 刘云2008北京交通大学学报2 67]

    [15]

    Ye Z L, Wang X Q, Wang X L, Li J 2010 Complex Systems and Complexity Science 1 (in Chinese)[叶作亮, 王雪乔, 王仙玲, 李静2010复杂系统与复杂性科学 01 (in Chinese)]

    [16]

    Zhou T, Liu J G, Bai W J, Chen G R, Wang B H 2006 Phys. Rev. E 74 056109

    [17]

    Barrett C, Eubank S, Marathe MV 2005 Modeling and simulation of large biological, information and socio-technical systems: an interaction based approach (Springer Verlag)

    [18]

    Crepey P, Barth′elemy M 2007 Am. J. Epidemiol. 166 1244

    [19]

    Ferguson N M, Cummings D A, Cauchemez S, Fraser C, Riley S, Meeyai A, Iamsirithaworn S, Burke D S 2005 Nature 437 209

    [20]

    Tang M, Liu L, Liu Z H, 2009 Phys. Rev. E 79 016108

    [21]

    Tang M, Liu Z H, Li B W 2009 Europhys. Lett. 87 18005

    [22]

    Zipf G K 1949 Human Behavior and the Principle of Least Effort (Addison-Wesley)

    [23]

    Zipf G K 1968 The Psycho-Biology of Language: An Introduction to Dynamic Psychology (Addison-Wesky)

    [24]

    Cattuto C, Loreto V, Pietronero L 2007 PNAS 104 1461

    [25]

    L¨u L Y, Zhang Z K, Zhou T 2010 PLoS One 5 e14139

    [26]

    Blasius B, Tonjes R 2009 Phys. Rev. Lett. 103 218701

    [27]

    Shao J, Lvanov P C, UrosevicUroˇsevi′c, Stanley H E, Podobnik B 2011 Europhys. Lett. 84 48001

    [28]

    Liu H K, Zhou T 2007 Acta Phys. Sin. 56 106 (in Chinese)[刘宏鲲, 周涛2007 56 1 06]

    [29]

    Reed W J 2003 Physica A 319 469

    [30]

    Reed W J, Jorgensen M 2004 Stats-Theory & Methods 33 1733

    [31]

    Han X P, Wang B H, Zhou C S, Zhou T, Zhu J F 2009 e-print arXiv. 0912.1390

    [32]

    Kendall M 1938 Biometrika 30 81

    [33]

    Shannon C E 1951 Bell Systems Technical Journal 30 50

    [34]

    Thomas M C 2006 Elements of Information Theory (Wiley)

    [35]

    Colizza V, Barrat A, Barthelemy M, Vespignani A 2006 PNAS 103 2015

    [36]

    Li M J, Wu Y, Liu W Q, Xiao J H 2009 Acta. Phys. Sin. 58 8 (in Chinese)[李明杰, 昊晔, 刘维清, 肖井华2009 58 8]

    [37]

    Xiong F, Liu Y, Si X M, Ding F 2010 Acta. Phys. Sin. 59 10 (in Chinese)[熊菲, 刘云, 司夏萌, 丁飞2010 59 10]

  • [1]

    Castellano C, Fortunato S, Loreto V 2009 Rev. Mod. Phys. 81 591

    [2]

    Zhou T,Wang B H, Han X P, Shang M S 2010 Jour. Syst. Eng. 25 742 (in Chinese)[周涛, 汪秉宏, 韩筱璞, 尚明生2010系统工程学报25 742]

    [3]

    Moreno Y, Nekovee M, Pacheco A F 2004 Phys. Rev. E 69 066130

    [4]

    Eubank S, Guclu H, Kumar V S A, Marthe M V, Srinivasan A, Toroczkai Z,Wang N 2004 Nature 429 180

    [5]

    Liu J Z, Wu J S, Yang Z R 2004 Physica A 341 273

    [6]

    Zheng D F, Hui PM, Trimper S, Zheng B 2005 Physica A 352 659

    [7]

    Sznajd W K, Sznajd J 2000 Int. J. Mod. Phys. C 11 1157

    [8]

    Deffuant G, Neau D, Amblard F, Weisbuch G 2000 Adv. Compl. Sys. 3 87

    [9]

    Galam S 2008 Int. J. Mod. Phys. C 19 409

    [10]

    H Kesten, V Sidoravicius 2005 Annals Prob 33 2402

    [11]

    Zhou J, Liu Z H, Li B 2007 Phys. Lett. A 368 458

    [12]

    Pan Z F, Wang X F, Li X 2006 Jornal of System Simulation 18 2346 (in Chinese)[潘灶烽, 汪小帆, 李翔2006系统仿真学报18 2346]

    [13]

    He M H, Zhang D M, Wang H Y, Li X G 2010 Acta Phys. Sin. 59 5175 (in Chinese)[何敏华, 张端明, 王海艳, 李小刚, 方频捷2010 59 5175]

    [14]

    Zhang L, Liu Y 2008 Journal of Beijing Jiaotong University. 2 67 (in Chinese)[张力, 刘云2008北京交通大学学报2 67]

    [15]

    Ye Z L, Wang X Q, Wang X L, Li J 2010 Complex Systems and Complexity Science 1 (in Chinese)[叶作亮, 王雪乔, 王仙玲, 李静2010复杂系统与复杂性科学 01 (in Chinese)]

    [16]

    Zhou T, Liu J G, Bai W J, Chen G R, Wang B H 2006 Phys. Rev. E 74 056109

    [17]

    Barrett C, Eubank S, Marathe MV 2005 Modeling and simulation of large biological, information and socio-technical systems: an interaction based approach (Springer Verlag)

    [18]

    Crepey P, Barth′elemy M 2007 Am. J. Epidemiol. 166 1244

    [19]

    Ferguson N M, Cummings D A, Cauchemez S, Fraser C, Riley S, Meeyai A, Iamsirithaworn S, Burke D S 2005 Nature 437 209

    [20]

    Tang M, Liu L, Liu Z H, 2009 Phys. Rev. E 79 016108

    [21]

    Tang M, Liu Z H, Li B W 2009 Europhys. Lett. 87 18005

    [22]

    Zipf G K 1949 Human Behavior and the Principle of Least Effort (Addison-Wesley)

    [23]

    Zipf G K 1968 The Psycho-Biology of Language: An Introduction to Dynamic Psychology (Addison-Wesky)

    [24]

    Cattuto C, Loreto V, Pietronero L 2007 PNAS 104 1461

    [25]

    L¨u L Y, Zhang Z K, Zhou T 2010 PLoS One 5 e14139

    [26]

    Blasius B, Tonjes R 2009 Phys. Rev. Lett. 103 218701

    [27]

    Shao J, Lvanov P C, UrosevicUroˇsevi′c, Stanley H E, Podobnik B 2011 Europhys. Lett. 84 48001

    [28]

    Liu H K, Zhou T 2007 Acta Phys. Sin. 56 106 (in Chinese)[刘宏鲲, 周涛2007 56 1 06]

    [29]

    Reed W J 2003 Physica A 319 469

    [30]

    Reed W J, Jorgensen M 2004 Stats-Theory & Methods 33 1733

    [31]

    Han X P, Wang B H, Zhou C S, Zhou T, Zhu J F 2009 e-print arXiv. 0912.1390

    [32]

    Kendall M 1938 Biometrika 30 81

    [33]

    Shannon C E 1951 Bell Systems Technical Journal 30 50

    [34]

    Thomas M C 2006 Elements of Information Theory (Wiley)

    [35]

    Colizza V, Barrat A, Barthelemy M, Vespignani A 2006 PNAS 103 2015

    [36]

    Li M J, Wu Y, Liu W Q, Xiao J H 2009 Acta. Phys. Sin. 58 8 (in Chinese)[李明杰, 昊晔, 刘维清, 肖井华2009 58 8]

    [37]

    Xiong F, Liu Y, Si X M, Ding F 2010 Acta. Phys. Sin. 59 10 (in Chinese)[熊菲, 刘云, 司夏萌, 丁飞2010 59 10]

  • [1] 汪亭亭, 梁宗文, 张若曦. 基于信息熵与迭代因子的复杂网络节点重要性评价方法.  , 2023, 72(4): 048901. doi: 10.7498/aps.72.20221878
    [2] 李丽娟, 明飞, 宋学科, 叶柳, 王栋. 熵不确定度关系综述.  , 2022, 71(7): 070302. doi: 10.7498/aps.71.20212197
    [3] 宋人杰, 袁紫燕, 张琪, 于洁, 薛洪惠, 屠娟, 章东. 基于超声RF信号熵分析的声空化时空监测方法.  , 2022, 71(17): 174301. doi: 10.7498/aps.71.20220558
    [4] 窦健泰, 高志山, 马骏, 袁操今, 杨忠明. 基于图像信息熵的ptychography轴向距离误差校正.  , 2017, 66(16): 164203. doi: 10.7498/aps.66.164203
    [5] 王金龙, 刘方爱, 朱振方. 一种基于用户相对权重的在线社交网络信息传播模型.  , 2015, 64(5): 050501. doi: 10.7498/aps.64.050501
    [6] 黄飞虎, 彭舰, 宁黎苗. 基于信息熵的社交网络观点演化模型.  , 2014, 63(16): 160501. doi: 10.7498/aps.63.160501
    [7] 李先锐, 朱彦丽. DC-DC变换器的信息熵分析.  , 2014, 63(23): 238401. doi: 10.7498/aps.63.238401
    [8] 胡兆龙, 刘建国, 任卓明. 基于节点度信息的自愿免疫模型研究.  , 2013, 62(21): 218901. doi: 10.7498/aps.62.218901
    [9] 焦一鸣, 周艳, 李永高, 李长征. 如何从偏振仪测量信息中获得q分布.  , 2012, 61(21): 215201. doi: 10.7498/aps.61.215201
    [10] 谢文贤, 蔡力, 岳晓乐, 雷佑铭, 徐伟. 两种群随机动力系统的信息熵和动力学研究.  , 2012, 61(17): 170509. doi: 10.7498/aps.61.170509
    [11] 陆坤权, 厚美瑛, 王强, 姜泽辉, 刘寄星. 震前兆信息传播、分布及其探测原理.  , 2011, 60(11): 119101. doi: 10.7498/aps.60.119101
    [12] 张彦超, 刘云, 张海峰, 程辉, 熊菲. 基于在线社交网络的信息传播模型.  , 2011, 60(5): 050501. doi: 10.7498/aps.60.050501
    [13] 冯爱霞, 龚志强, 黄琰, 王启光. 全球温度场信息熵的时空特征分析.  , 2011, 60(9): 099204. doi: 10.7498/aps.60.099204
    [14] 郭永峰, 徐伟, 李东喜, 王亮. 准单色噪声驱动的耗散动力系统的信息熵演化.  , 2010, 59(4): 2235-2239. doi: 10.7498/aps.59.2235
    [15] 张春涛, 马千里, 彭宏. 基于信息熵优化相空间重构参数的混沌时间序列预测.  , 2010, 59(11): 7623-7629. doi: 10.7498/aps.59.7623
    [16] 郭培荣, 徐伟, 刘迪. 非高斯噪声驱动的双奇异随机系统的熵流与熵产生.  , 2009, 58(8): 5179-5185. doi: 10.7498/aps.58.5179
    [17] 方小玲, 姜宗来. 基于脑电图的大脑功能性网络分析.  , 2007, 56(12): 7330-7338. doi: 10.7498/aps.56.7330
    [18] 郭永峰, 徐 伟, 李东喜. 色噪声驱动的双奇异随机系统随时间演化的熵变化率上界.  , 2007, 56(10): 5613-5617. doi: 10.7498/aps.56.5613
    [19] 刘小娟, 周并举, 方卯发, 周清平. 双光子过程中任意初态原子的信息熵压缩.  , 2006, 55(2): 704-711. doi: 10.7498/aps.55.704
    [20] 谢文贤, 徐 伟, 蔡 力. 色噪声驱动的双奇异随机系统的熵流与熵产生.  , 2006, 55(4): 1639-1643. doi: 10.7498/aps.55.1639
计量
  • 文章访问数:  9424
  • PDF下载量:  1489
  • 被引次数: 0
出版历程
  • 收稿日期:  2011-07-17
  • 修回日期:  2012-05-10
  • 刊出日期:  2012-05-05

/

返回文章
返回
Baidu
map