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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.
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Keywords:
- online public opinion /
- attention /
- Zipf distribution /
- information entropy
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[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
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[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
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[32] Kendall M 1938 Biometrika 30 81
[33] Shannon C E 1951 Bell Systems Technical Journal 30 50
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[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物理学报58 8]
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[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物理学报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物理学报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物理学报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物理学报59 10]
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