基于BDI-Agent模型的网民集群行为建模研究
|
摘要
面向网络舆情演变过程中网民集群行为的政府应急响应需求,文章基于"信念—愿望—意图"模型(Belief-Desire-Intention,BDI)和网民集群行为理论,设计网民集群的BDI-Agent行为推理模型,用信念、愿望和意图描述和推理网民的集群行为决策。考虑不同类型的网民信念、愿望的差异以及网民集群行为影响因素,本文把参与集群的网民分为4类:"独立型—初始接受""独立型—初始拒绝""交互型—初始接受"和"交互型—初始拒绝",并结合信息源、群体压力和个体预期三个影响因素进行建模。在此基础上,结合突发事件案例进行仿真实验,并和案例中网民集群行为真实舆情数据进行对比验证,并应用多元方差分析了不同类型突发事件主题对网民集群行为的影响。最后,本文研究了不同政府调节措施对网民集群的调节作用,为突发事件应急响应决策提供参考。
To meet the demands of government emergency response for online users' collective behaviors in the evolution of network public opinions,a BDI-Agent model is designed to reason the generation of network collective behaviors based on the theory of BDI model(Belief-Desire-Intention) and the network collective behavior theory.Belief,desire and intention are used to describe and reason the network users' collective behavior decisions.The users are divided into four types according to the influencing factors of collective behaviors as well as their differences in belief,desire and intention,including "the independent-initial acceptance users","the independent-initial refusal users","the interactive-initial acceptance users",and "the interactive-initial refusal users".The influencing factors such as information source,group pressure,and individual expectations are also taken into consideration to construct the model.Based on this,the simulation experiments of emergency events are carried out,the results of which are compared with the real public opinion data of online users' collective behavior to verify the model.Also,the paper analyzes the influence of different types of emergencies on network collective behaviors by multivariate variance.Finally,the regulation effect of different government response strategies on the network collective behavior is discussed,which could support to the emergency response decision-making.
To meet the demands of government emergency response for online users' collective behaviors in the evolution of network public opinions,a BDI-Agent model is designed to reason the generation of network collective behaviors based on the theory of BDI model(Belief-Desire-Intention) and the network collective behavior theory.Belief,desire and intention are used to describe and reason the network users' collective behavior decisions.The users are divided into four types according to the influencing factors of collective behaviors as well as their differences in belief,desire and intention,including "the independent-initial acceptance users","the independent-initial refusal users","the interactive-initial acceptance users",and "the interactive-initial refusal users".The influencing factors such as information source,group pressure,and individual expectations are also taken into consideration to construct the model.Based on this,the simulation experiments of emergency events are carried out,the results of which are compared with the real public opinion data of online users' collective behavior to verify the model.Also,the paper analyzes the influence of different types of emergencies on network collective behaviors by multivariate variance.Finally,the regulation effect of different government response strategies on the network collective behavior is discussed,which could support to the emergency response decision-making.
引文
[1] 董贝蓓.心理不安全感、群体认同对网民集群行为意向的影响[D].北京:中国地质大学(北京),2016.
[2] 屈亚琴.社会网络中舆情传播的集群行为演化研究[D].湘潭:湘潭大学,2015.
[3] 师亚凯,马慧芳,张迪,等.融合用户行为和内容的微博用户影响力方法[J].计算机应用研究,2016,33(10):2906-2909.
[4] 程荣晖.大众传媒对网民集群行为的引导策略[J].传媒,2017(5):85-87.
[5] 钱晓蓉.公共管理中网民集群行为的研究[D].苏州:苏州大学,2011.
[6] 孟奂.网民集群行为演变过程研究——以手术台自拍事件网络传播为例[J].新闻研究导刊,2016,7(22):118-118.
[7] 赵卫东,赵旭东,戴伟辉,等.突发事件的网络情绪传播机制及仿真研究[J].系统工程理论与实践,2015,35(10):2573-2581.
[8] 栾劲松.社会认同视角下大学生集群行为影响因素的研究[D].长春:吉林大学,2014.
[9] HOMANS G C.Theory of collective behavior[J].American Political Science Review,1963,57(4):957-958.
[10] 沈晖.网民集群行为与社会工作介入策略[J].中国地质大学学报:社会科学版,2009,9(5):94-99.
[11] SHI J,LAI K K,HU P,et al.Understanding and predicting individual retweeting behavior:receiver perspectives[J].Applied Soft Computing,2017(4).
[12] 朱肖维.混合网络环境下网民集群行为混合网络环境下网民集群行为的实证研究[D].上海:上海交通大学,2010.
[13] NEPPALLI V K,CARAGEA C,SQUICCIARINI A,et al.Sentiment analysis during hurricane sandy in emergency response[J].International Journal of Disaster Risk Reduction,2017,21:213-222.
[14] 李根强,刘人境,孟勇,等.社会网络视角下思维聚焦对集群行为发展趋势的影响[J].软科学,2017,31(7):126-130.
[15] HOPP T,VARGO C J.Does negative campaign advertising stimulate uncivil communication on social media?Measuring audience response using big data[J].Computers in Human Behavior,2017,68:368-377.
[16] R?SNER L,WINTER S,KR?MER N C.Dangerous minds?Effects of uncivil online comments on aggressive cognitions,emotions,and behavior[J].Computers in Human Behavior,2016,58:461-470.
[17] CHO V.A study of negative emotional disclosure behavior in social network media:Will an unexpected negative event and personality matter?[J].Computers in Human Behavior,2017,73.
[18] FAYAZI M,HASANI J.Structural relations between brain-behavioral systems,social anxiety,depression and internet addiction:With regard to revised Reinforcement Sensitivity Theory (r-RST) [J].Computers in Human Behavior,2017,72:441-448.
[19] KRAAYENBRINK N,KESSING J,TUTENEL T,et al.Semantic crowds:reusable population for virtual worlds[J].Procedia Computer Science,2012,15(2):122-139.
[20] LEVESQUE C H J.Intention is choice with commitment[J].Artificial Intelligence,1990,42(2):213-261.
[21] CASALI A,GODO L,SIERRA C.A graded BDI agent model to represent and reason about preferences[J].Artificial Intelligence,2011,175(7):1468-1478.
[22] 张晓君,周昌乐.情感等级BDI主体模型研究[J].模式识别与人工智能,2013,26(7):615-622.
[23] 孔博枢.基于情感BDI模型的Agent行为控制研究[D].长沙:湖南大学,2016.
[24] CRIADO N,ARGENTE E,NORIEGA P,et al.Human-inspired model for norm compliance decision making[J].Information Sciences,2013,245:218-239.
[25] 吴鹏,金贝贝,强韶华.基于BDI-Agent模型的突发事件网络舆情应急响应建模研究[J].现代图书情报技术,2016,32(S1):32-41.
[26] COOMBS W T.The protective powers of crisis response strategies:managing reputational assets during a crisis[J].Journal of Promotion Management,2006,12(3/4):241-260.
[27] COOMBS W T.Protecting organization reputations during a crisis:the development and application of situational crisis communication theory[J].Corporate Reputation Review,2007,10(3):163-176.
[28] JIN Y,LIU B F.The blog-mediated crisis communication model:recommendations for responding to influential external blogs[J].Journal of Public Relations Research,2010,22(4):429-455.
[29] NAAMAN M,BOASE J,LAI C-H.Is it really about me?Message content in social awareness streams[C]//Proceedings of the 2010 ACM Conference On Computer Supported Cooperative Work,F,2010.
[2] 屈亚琴.社会网络中舆情传播的集群行为演化研究[D].湘潭:湘潭大学,2015.
[3] 师亚凯,马慧芳,张迪,等.融合用户行为和内容的微博用户影响力方法[J].计算机应用研究,2016,33(10):2906-2909.
[4] 程荣晖.大众传媒对网民集群行为的引导策略[J].传媒,2017(5):85-87.
[5] 钱晓蓉.公共管理中网民集群行为的研究[D].苏州:苏州大学,2011.
[6] 孟奂.网民集群行为演变过程研究——以手术台自拍事件网络传播为例[J].新闻研究导刊,2016,7(22):118-118.
[7] 赵卫东,赵旭东,戴伟辉,等.突发事件的网络情绪传播机制及仿真研究[J].系统工程理论与实践,2015,35(10):2573-2581.
[8] 栾劲松.社会认同视角下大学生集群行为影响因素的研究[D].长春:吉林大学,2014.
[9] HOMANS G C.Theory of collective behavior[J].American Political Science Review,1963,57(4):957-958.
[10] 沈晖.网民集群行为与社会工作介入策略[J].中国地质大学学报:社会科学版,2009,9(5):94-99.
[11] SHI J,LAI K K,HU P,et al.Understanding and predicting individual retweeting behavior:receiver perspectives[J].Applied Soft Computing,2017(4).
[12] 朱肖维.混合网络环境下网民集群行为混合网络环境下网民集群行为的实证研究[D].上海:上海交通大学,2010.
[13] NEPPALLI V K,CARAGEA C,SQUICCIARINI A,et al.Sentiment analysis during hurricane sandy in emergency response[J].International Journal of Disaster Risk Reduction,2017,21:213-222.
[14] 李根强,刘人境,孟勇,等.社会网络视角下思维聚焦对集群行为发展趋势的影响[J].软科学,2017,31(7):126-130.
[15] HOPP T,VARGO C J.Does negative campaign advertising stimulate uncivil communication on social media?Measuring audience response using big data[J].Computers in Human Behavior,2017,68:368-377.
[16] R?SNER L,WINTER S,KR?MER N C.Dangerous minds?Effects of uncivil online comments on aggressive cognitions,emotions,and behavior[J].Computers in Human Behavior,2016,58:461-470.
[17] CHO V.A study of negative emotional disclosure behavior in social network media:Will an unexpected negative event and personality matter?[J].Computers in Human Behavior,2017,73.
[18] FAYAZI M,HASANI J.Structural relations between brain-behavioral systems,social anxiety,depression and internet addiction:With regard to revised Reinforcement Sensitivity Theory (r-RST) [J].Computers in Human Behavior,2017,72:441-448.
[19] KRAAYENBRINK N,KESSING J,TUTENEL T,et al.Semantic crowds:reusable population for virtual worlds[J].Procedia Computer Science,2012,15(2):122-139.
[20] LEVESQUE C H J.Intention is choice with commitment[J].Artificial Intelligence,1990,42(2):213-261.
[21] CASALI A,GODO L,SIERRA C.A graded BDI agent model to represent and reason about preferences[J].Artificial Intelligence,2011,175(7):1468-1478.
[22] 张晓君,周昌乐.情感等级BDI主体模型研究[J].模式识别与人工智能,2013,26(7):615-622.
[23] 孔博枢.基于情感BDI模型的Agent行为控制研究[D].长沙:湖南大学,2016.
[24] CRIADO N,ARGENTE E,NORIEGA P,et al.Human-inspired model for norm compliance decision making[J].Information Sciences,2013,245:218-239.
[25] 吴鹏,金贝贝,强韶华.基于BDI-Agent模型的突发事件网络舆情应急响应建模研究[J].现代图书情报技术,2016,32(S1):32-41.
[26] COOMBS W T.The protective powers of crisis response strategies:managing reputational assets during a crisis[J].Journal of Promotion Management,2006,12(3/4):241-260.
[27] COOMBS W T.Protecting organization reputations during a crisis:the development and application of situational crisis communication theory[J].Corporate Reputation Review,2007,10(3):163-176.
[28] JIN Y,LIU B F.The blog-mediated crisis communication model:recommendations for responding to influential external blogs[J].Journal of Public Relations Research,2010,22(4):429-455.
[29] NAAMAN M,BOASE J,LAI C-H.Is it really about me?Message content in social awareness streams[C]//Proceedings of the 2010 ACM Conference On Computer Supported Cooperative Work,F,2010.