The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related in...The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.展开更多
Accurately simulating large-scale user behavior is important to improve the similarity between the cyber range and the real network environment. The Linux Container provides a method to simulate the behavior of large-...Accurately simulating large-scale user behavior is important to improve the similarity between the cyber range and the real network environment. The Linux Container provides a method to simulate the behavior of large-scale users under the constraints of limited physical resources. In a container-based virtualization environment, container networking is an important component. To evaluate the impact of different networking methods between the containers on the simulation performance, the typical container networking methods such as none, bridge, macvlan were analyzed, and the performance of different networking methods was evaluated according to the throughput and latency metrics. The experiments show that under the same physical resource constraints, the macvlan networking method has the best network performance, while the bridge method has the worst performance. This result provides a reference for selecting the appropriate networking method in the user behavior simulation process.展开更多
This paper explores the uses’ influences on microblog. At first, according to the social network theory, we present an analysis of information transmitting network structure based on the relationship of following and...This paper explores the uses’ influences on microblog. At first, according to the social network theory, we present an analysis of information transmitting network structure based on the relationship of following and followed phenomenon of microblog users. Informed by the microblog user behavior analysis, the paper also addresses a model for calculating weights of users’ influence. It proposes a U-R model, using which we can evaluate users’ influence based on PageRank algorithms and analyzes user behaviors. In the U-R model, the effect of user behaviors is explored and PageRank is applied to evaluate the importance and the influence of every user in a microblog network by repeatedly iterating their own U-R value. The users’ influences in a microblog network can be ranked by the U-R value. Finally, the validity of U-R model is proved with a real-life numerical example.展开更多
The problem of privacy in social networks is well documented within literature;users have pri- vacy concerns however, they consistently disclose their sensitive information and leave it open to unintended third partie...The problem of privacy in social networks is well documented within literature;users have pri- vacy concerns however, they consistently disclose their sensitive information and leave it open to unintended third parties. While numerous causes of poor behaviour have been suggested by re- search the role of the User Interface (UI) and the system itself is underexplored. The field of Per- suasive Technology would suggest that Social Network Systems persuade users to deviate from their normal or habitual behaviour. This paper makes the case that the UI can be used as the basis for user empowerment by informing them of their privacy at the point of interaction and remind- ing them of their privacy needs. The Theory of Planned Behaviour is introduced as a potential theoretical foundation for exploring the psychology behind privacy behaviour as it describes the salient factors that influence intention and action. Based on these factors of personal attitude, subjective norms and perceived control, a series of UIs are presented and implemented in con- trolled experiments examining their effect on personal information disclosure. This is combined with observations and interviews with the participants. Results from this initial, pilot experiment suggest groups with privacy salient information embedded exhibit less disclosure than the control group. This work reviews this approach as a method for exploring privacy behaviour and propos- es further work required.展开更多
Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which inf...Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which influence knowledge contribution behavior of social networking sites(SNS) users.Design/methodology/approach: The data were obtained from an online survey of 251 social networking sites users. Structural equation modeling analysis was used to validate the proposed model.Findings: Our survey shows that the individuals' motivation for knowledge contribution,their capability of contributing knowledge,interpersonal trust and their own habits positively influence their knowledge contribution behavior,but reward does not significantly influence knowledge contribution in the online virtual community.Research limitations: Respondents of our online survey are mainly undergraduate and graduate students. A limited sample group cannot represent all of the population. A larger survey involving more SNS users may be useful.Practical implications: The results have provided some theoretical basis for promoting knowledge contribution and user viscosity.Originality/value: Few studies have investigated the impact of social influence and user habits on knowledge contribution behavior of SNS users. This study can make a theoretical contribution by examining how the social influence processes and habits affect one's knowledge contribution behavior using online communities.展开更多
电力用户行为数据维度高、特征间存在共线性,导致信息冗余和分析精度下降,影响检测效果。为了有效确保电网的安全和稳定运行,提出一种基于反向传播(Back Propagation,BP)神经网络的电力用户异常用电行为检测方法。构建正常用电行为基准...电力用户行为数据维度高、特征间存在共线性,导致信息冗余和分析精度下降,影响检测效果。为了有效确保电网的安全和稳定运行,提出一种基于反向传播(Back Propagation,BP)神经网络的电力用户异常用电行为检测方法。构建正常用电行为基准模型,刻画时空特征以识别偏离行为。针对特征差异,提出最优特征评价模型,通过优选机制降维、解决共线性问题,用信息熵量化特征贡献度并归一化处理,迭代筛选强判别性特征子集。随后,基于K-means聚类分析用户电力特征数据,实现用户分群。引入随机矩阵理论评估用户行为模式影响因素。用电行为刻画后,采用BP神经网络检测异常,针对高维特征,用子空间聚类算法划分空间,BP神经网络通过迭代优化训练模型,调整权重参数完成检测。实验研究表明,本文方法聚类效果最佳,贝叶斯检出率受迭代次数影响小,稳定性强,检测性能更优;ROC曲线下的面积(Area Under the Curve,AUC)值更接近1。在电力用户异常用电行为检测方面性能良好,可以得到高准确率的检测结果。展开更多
基金sponsored by the National Natural Science Foundation of China under grant number No.61100008,61201084the China Postdoctoral Science Foundation under Grant No.2013M541346+3 种基金Heilongiiang Postdoctoral Special Fund(Postdoctoral Youth Talent Program)under Grant No.LBH-TZ0504Heilongjiang Postdoctoral Fund under Grant No.LBH-Z13058the Natural Science Foundation of Heilongjiang Province of China under Grant No.QC2015076The Fundamental Research Funds for the Central Universities of China under grant number HEUCF100602
文摘The e-mail network is a type of social network. This study analyzes user behavior in e-mail subject participation in organizations by using social network analysis. First, the Enron dataset and the position-related information of an employee are introduced, and methods for deletion of false data are presented. Next, the three-layer model(User, Subject, Keyword) is proposed for analysis of user behavior. Then, the proposed keyword selection algorithm based on a greedy approach, and the influence and propagation of an e-mail subject are defined. Finally, the e-mail user behavior is analyzed for the Enron organization. This study has considerable significance in subject recommendation and character recognition.
文摘Accurately simulating large-scale user behavior is important to improve the similarity between the cyber range and the real network environment. The Linux Container provides a method to simulate the behavior of large-scale users under the constraints of limited physical resources. In a container-based virtualization environment, container networking is an important component. To evaluate the impact of different networking methods between the containers on the simulation performance, the typical container networking methods such as none, bridge, macvlan were analyzed, and the performance of different networking methods was evaluated according to the throughput and latency metrics. The experiments show that under the same physical resource constraints, the macvlan networking method has the best network performance, while the bridge method has the worst performance. This result provides a reference for selecting the appropriate networking method in the user behavior simulation process.
文摘This paper explores the uses’ influences on microblog. At first, according to the social network theory, we present an analysis of information transmitting network structure based on the relationship of following and followed phenomenon of microblog users. Informed by the microblog user behavior analysis, the paper also addresses a model for calculating weights of users’ influence. It proposes a U-R model, using which we can evaluate users’ influence based on PageRank algorithms and analyzes user behaviors. In the U-R model, the effect of user behaviors is explored and PageRank is applied to evaluate the importance and the influence of every user in a microblog network by repeatedly iterating their own U-R value. The users’ influences in a microblog network can be ranked by the U-R value. Finally, the validity of U-R model is proved with a real-life numerical example.
文摘The problem of privacy in social networks is well documented within literature;users have pri- vacy concerns however, they consistently disclose their sensitive information and leave it open to unintended third parties. While numerous causes of poor behaviour have been suggested by re- search the role of the User Interface (UI) and the system itself is underexplored. The field of Per- suasive Technology would suggest that Social Network Systems persuade users to deviate from their normal or habitual behaviour. This paper makes the case that the UI can be used as the basis for user empowerment by informing them of their privacy at the point of interaction and remind- ing them of their privacy needs. The Theory of Planned Behaviour is introduced as a potential theoretical foundation for exploring the psychology behind privacy behaviour as it describes the salient factors that influence intention and action. Based on these factors of personal attitude, subjective norms and perceived control, a series of UIs are presented and implemented in con- trolled experiments examining their effect on personal information disclosure. This is combined with observations and interviews with the participants. Results from this initial, pilot experiment suggest groups with privacy salient information embedded exhibit less disclosure than the control group. This work reviews this approach as a method for exploring privacy behaviour and propos- es further work required.
基金supported by the National Social Science Foundation of China(Grant Nos.:10CTQ010 and 11CTQ038)Wuhan University Development Program for Researchers Born after the 1970s
文摘Purpose: In the Web 2.0 era,leveraging the collective power of user knowledge contributions has become an important part of the study of collective intelligence. This research aims to investigate the factors which influence knowledge contribution behavior of social networking sites(SNS) users.Design/methodology/approach: The data were obtained from an online survey of 251 social networking sites users. Structural equation modeling analysis was used to validate the proposed model.Findings: Our survey shows that the individuals' motivation for knowledge contribution,their capability of contributing knowledge,interpersonal trust and their own habits positively influence their knowledge contribution behavior,but reward does not significantly influence knowledge contribution in the online virtual community.Research limitations: Respondents of our online survey are mainly undergraduate and graduate students. A limited sample group cannot represent all of the population. A larger survey involving more SNS users may be useful.Practical implications: The results have provided some theoretical basis for promoting knowledge contribution and user viscosity.Originality/value: Few studies have investigated the impact of social influence and user habits on knowledge contribution behavior of SNS users. This study can make a theoretical contribution by examining how the social influence processes and habits affect one's knowledge contribution behavior using online communities.
文摘电力用户行为数据维度高、特征间存在共线性,导致信息冗余和分析精度下降,影响检测效果。为了有效确保电网的安全和稳定运行,提出一种基于反向传播(Back Propagation,BP)神经网络的电力用户异常用电行为检测方法。构建正常用电行为基准模型,刻画时空特征以识别偏离行为。针对特征差异,提出最优特征评价模型,通过优选机制降维、解决共线性问题,用信息熵量化特征贡献度并归一化处理,迭代筛选强判别性特征子集。随后,基于K-means聚类分析用户电力特征数据,实现用户分群。引入随机矩阵理论评估用户行为模式影响因素。用电行为刻画后,采用BP神经网络检测异常,针对高维特征,用子空间聚类算法划分空间,BP神经网络通过迭代优化训练模型,调整权重参数完成检测。实验研究表明,本文方法聚类效果最佳,贝叶斯检出率受迭代次数影响小,稳定性强,检测性能更优;ROC曲线下的面积(Area Under the Curve,AUC)值更接近1。在电力用户异常用电行为检测方面性能良好,可以得到高准确率的检测结果。
