开放互联网环境基于信息熵的信息传播影响力计算方法

doi:10.11959/j.issn.1000-0801.2022026

电信科学 ›› 2022, Vol. 38 ›› Issue (4): 90-100.doi: 10.11959/j.issn.1000-0801.2022026

开放互联网环境基于信息熵的信息传播影响力计算方法

李攀攀¹, 谢正霞², 王赠凯¹, 靳锐³

¹ 嘉兴学院信息科学与工程学院，浙江嘉兴 314001
² 嘉兴学院建筑工程学院，浙江嘉兴 314001
³ 哈尔滨工业大学计算机科学与技术学院，黑龙江哈尔滨 150001

修回日期:2022-01-29 出版日期:2022-04-20 发布日期:2022-04-01
作者简介:李攀攀（1983− ），男，博士，嘉兴学院信息科学与工程学院讲师，主要研究方向为社会计算、网络空间安全、人工智能等
谢正霞（1982− ），女，嘉兴学院建筑工程学院工程师，主要研究方向为社会计算、网络舆情等
王赠凯（1980− ），男，博士，嘉兴学院信息科学与工程学院讲师，主要研究方向为社会计算、人工智能等
靳锐（1976− ），男，哈尔滨工业大学计算机科学与技术学院博士生，主要研究方向为信息安全、社交网络分析、机器学习等
基金资助:
国家自然科学基金资助项目(61902226);浙江省自然科学基金资助项目(LY18F020021)

Calculation method of information dissemination based on information entropy in public internet

Panpan LI¹, Zhengxia XIE², Zengkai WANG¹, Rui JIN³

¹ College of Information Science and Engineering, Jiaxing University, Jiaxing 314001, China
² College of CML Engineering and Architecture, Jiaxing University, Jiaxing 314001, China
³ School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China

Revised:2022-01-29 Online:2022-04-20 Published:2022-04-01
Supported by:
The National Natural Science Foundation of China(61902226);The Natural Science Foundation of Zhejiang Province(LY18F020021)

摘要/Abstract

摘要：

研究了开放互联网环境下衡量信息传播的影响力，提出了一种基于最大熵理论的信息传播影响力计算方法。首先，对信息传播影响力所涉及的要素进行建模；然后，以香农信息熵理论为基础，根据“奥卡姆剃刀原理”选取信息影响力关联指标；最后，基于信息熵理论给出了信息传播影响力的计算方法。对学术论文引文和网络舆情事件的传播影响力进行了分析，验证了所提方法的有效性，所提方法对探究信息在开放互联网环境中的传播影响力以及对受众的影响程度具有重要的现实意义。

关键词: 开放互联网, 传播影响力, 信息熵, 最大熵理论, 计算传播学

Abstract:

A method of how to calculate the influence of information dissemination based on the maximum entropy theory was presented, which aimed at evaluating the impacts of the information dissemination in the open internet environment.Firstly, the influential factors of the information dissemination were analyzed.Then, the factors that have high correlation with the calculation of information dissemination were selected by the principle of “Occam’s Razor”, based on Shannon's information entropy theory.Finally, the method of computing the influence of information dissemination was proposed based on the information entropy theory.The effectiveness of the proposed method was validated by the experiments of analyzing the influence of the information dissemination of academic paper citations and hot public opinion events.The experiments show that the proposed method is of great significance for investigating the influence of information dissemination and the extent of impacts on the audience as well as the trends of information evolution in the open internet environment.

Key words: public internet, communication influence, information entropy, maximum entropy theory, computational communication

中图分类号:

G206

李攀攀, 谢正霞, 王赠凯, 靳锐. 开放互联网环境基于信息熵的信息传播影响力计算方法[J]. 电信科学, 2022, 38(4): 90-100.

Panpan LI, Zhengxia XIE, Zengkai WANG, Rui JIN. Calculation method of information dissemination based on information entropy in public internet[J]. Telecommunications Science, 2022, 38(4): 90-100.

图/表 10

图1

图2

图3

图4

表1

图4-1

图5

图6

表2

图7

参考文献 25

[1]	中国互联网络信息中心. 第47次《中国互联网络发展状况统计报告》[R]. 2021.
	CNNIC. The 47th “Statistical Report on the Development of the Internet in China”[R]. 2021.
[2]	郭宇, 王晰巍, 李师萌 ,等. 基于情感分析的社会网络用户影响力模型研究[J]. 情报学报, 2017,36(11): 1139-1147.
	GUO Y , WANG X W , LI S M ,et al. Research on the influence model of social network users based on emotional analysis[J]. Journal of the China Society for Scientific and Technical Information, 2017,36(11): 1139-1147.
[3]	李根强, 刘莎, 张亚楠 ,等. 信息熵理论视角下网络集群行为主体的观点演化研究[J]. 情报科学, 2020,38(1): 42-47,86.
	LI G Q , LIU S , ZHANG Y N ,et al. Research on the opinion evolution in online collective behavior from the perspective of information entropy[J]. Information Science, 2020,38(1): 42-47,86.
[4]	GUILLE A , HACID H , FAVRE C ,et al. Information diffusion in online social networks[J]. ACM SIGMOD Record, 2013,42(2): 17-28.
[5]	方滨兴, 贾焰, 韩毅 . 社交网络分析核心科学问题、研究现状及未来展望[J]. 中国科学院院刊, 2015,30(2): 187-199.
	FANG B X , JIA Y , HAN Y . Social network analysis—key research problems,related work,and future prospects[J]. Bulletin of Chinese Academy of Sciences, 2015,30(2): 187-199.
[6]	靳锐, 张宏莉, 张玥 ,等. 中文公众事件信息熵计算方法[J]. 软件学报, 2016,27(11): 2855-2869.
	JIN R , ZHANG H L , ZHANG Y ,et al. Calculation method of Chinese public event information entropy[J]. Journal of Software, 2016,27(11): 2855-2869.
[7]	黄飞虎, 彭舰, 宁黎苗 . 基于信息熵的社交网络观点演化模型[J]. 物理学报, 2014,63(16): 160501.
	HUANG F H , PENG J , NING L M . Opinion evolution model of social network based on information entropy[J]. Acta Physica Sinica, 2014,63(16): 160501.
[8]	王祯骏, 王树徽, 张维刚 ,等. 基于社交内容的潜在影响力传播模型[J]. 计算机学报, 2016,39(8): 1528-1540.
	WANG Z J , WANG S H , ZHANG W G ,et al. Social content based latent influence propagation model[J]. Chinese Journal of Computers, 2016,39(8): 1528-1540.
[9]	SINGH S S , KUMAR A , SINGH K ,et al. LAPSO-IM:a learning-based influence maximization approach for social networks[J]. Applied Soft Computing, 2019(82): 105554.
[10]	SINGH S S , SINGH K , KUMAR A ,et al. ACO-IM:maximizing influence in social networks using ant colony optimization[J]. Soft Computing, 2020,24(13): 10181-10203.
[11]	吴吟, 孙瑱 . 互联网信息传播中的事件网络关键节点研究:一项基于网络拓扑学的实证研究[J]. 中国广播电视学刊, 2020(6): 37-42.
	WU Y , SUN T . A study of key nodes of event networks in internet information dissemination-an empirical study based on network topology[J]. China Radio ＆ TV Academic Journal, 2020(6): 37-42.
[12]	王晰巍, 贾若男, 刘婷艳 ,等. 新冠肺炎疫情事件信息传播主体特征分析方法及模型:以“钻石公主号邮轮”事件为例[J]. 情报学报, 2021,40(3): 245-255.
	WANG X W , JIA R N , LIU T Y ,et al. Research on the characteristics of the participants of information dissemination during the COVID-19 pandemic—a case study of “diamond princess”[J]. Journal of the China Society for Scientific and Technical Information, 2021,40(3): 245-255.
[13]	王晰巍, 张柳, 韦雅楠 ,等. 社交网络舆情中意见领袖主题图谱构建及关系路径研究:基于网络谣言话题的分析[J]. 情报资料工作, 2020(2): 47-55.
	WANG X W , ZHANG L , WEI Y N ,et al. Research on thematic map construction and relationship path of opinion leaders in social network public opinion:an analysis based on Internet rumor topics[J]. Information and Documentation Services, 2020(2): 47-55.
[14]	琚春华, 赵凯迪, 鲍福光 . 融入紧密度中心性与信用的社交网络用户影响力强度计算模型[J]. 情报学报, 2019,38(2): 170-177.
	JU C H , ZHAO K D , BAO F G . A user influence strength model in E-commerce social networks based on closeness and users’ credit[J]. Journal of the China Society for Scientific and Technical Information, 2019,38(2): 170-177.
[15]	YUAN J J , SHI J W , CHE J Y ,et al. Modeling and simulation analysis of public opinion polarization in a dynamic network environment[J]. Concurrency and Computation:Practice and Experience, 2020,32(19): e5771.
[16]	KEMPE D , KLEINBERG J , TARDOS é , . Maximizing the spread of influence through a social network[C]// KDD’03:Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining.[S.l.:s.n.], 2003: 137-146.
[17]	吴小兰, 章成志 . 基于社交媒体的高影响力跨学科用户发现研究[J]. 情报学报, 2017,36(6): 618-627.
	WU X L , ZHANG C Z . Finding high-impact interdisciplinary users based on social media[J]. Journal of the China Society for Scientific and Technical Information, 2017,36(6): 618-627.
[18]	朱毅华, 张超群 . 基于影响模型的网络舆情演化与传播仿真研究[J]. 情报杂志, 2015,34(2): 28-36.
	ZHU Y H , ZHANG C Q . An application of impact model to simulating the evolution and dissemination of network public opinion[J]. Journal of Intelligence, 2015,34(2): 28-36.
[19]	SHANNON C E . A mathematical theory of communication[J]. The Bell System Technical Journal, 1948,27(3): 379-423.
[20]	ZHANG H L , JIN R , ZHANG Y ,et al. A public psychological pressure index for social networks[J]. IEEE Access, 2020(8): 23457-23469.
[21]	吴瑞明, 胡代平 . 评价系统结构的信息熵方法[J]. 情报杂志, 2008,27(11): 3-6.
	WU R M , HU D P . The method of evaluating and choosing for systems structures based on entropy[J]. Journal of Information, 2008,27(11): 3-6.
[22]	RIM H , LEE Y , YOO S . Polarized public opinion responding to corporate social advocacy:social network analysis of boycotters and advocators[J]. Public Relations Review, 2020,46(2): 101869.
[23]	宋卓远, 阚乾超, 赵凯 ,等. 基于共词分析的国内文本挖掘研究[J]. 图书馆学刊, 2021,43(4): 104-111.
	SONG Z Y , KAN Q C , ZHAO K ,et al. Research on domestic text mining based on CO-word analysis[J]. Journal of Library Science, 2021,43(4): 104-111.
[24]	DBLP Computer Science Bibliography. DataBase systems and Logic Programming[EB]. 2021.
[25]	American Physical Society. APS data sets for research[EB]. 2021.

X_i	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉	X₁₀
c_i	c₁	c₂	c₃	c₄	c₅	c₆	c₇	c₈	c₉	c₁₀

时间	编号	舆情事件	来源
2019年	事件1	《啥是佩奇》爆红网络事件	新浪微博
	事件2	翟天临论文事件	社交网络
2020年	事件3	北京一女子开奔驰进故宫事件	新浪微博
	事件4	浙江温岭槽罐车爆炸事故	人民日报
2021年	事件5	比尔·盖茨离婚事件	新浪新闻
	事件6	第七次人口普查数据公布事件	新华社

开放互联网环境基于信息熵的信息传播影响力计算方法

Calculation method of information dissemination based on information entropy in public internet

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 25

相关文章 5

Metrics

推荐阅读 0

[1]	邢亚芬, 殷海兵, 王鸿奎, 骆琼华. 基于视频时域感知特性的恰可察觉失真模型[J]. 电信科学, 2022, 38(2): 92-102.
[2]	李攀攀, 谢正霞, 王赠凯, 靳锐. 一种基于信息DNA的互联网信息内容传播及演化追溯方法[J]. 电信科学, 2022, 38(11): 36-46.
[3]	陈铁明, 项彬彬, 吕明琪, 陈波, 江颉. 基于字节码图像和深度学习的Android恶意应用检测[J]. 电信科学, 2019, 35(1): 9-17.
[4]	汪敏娟,嵇正鹏,吕超. 基于预测度量值的IPTV用户行为规则预测算法[J]. 电信科学, 2016, 32(5): 160-165.
[5]	琚春华,邹江波. 基于信息熵差异性度量的数据流增量集成分类算法[J]. 电信科学, 2015, 31(2): 86-96.