Chaos in social learning with multiple true states

Most existing social learning models assume that there is only one underlying true state. In this work, we consider a social learning model with multiple true states, in which agents in different groups receive different signal sequences generated by their corresponding underlying true states. Each agent updates his belief by combining his rational self-adjustment based on the external signals he received and the influence of his neighbors according to their communication. We observe chaotic oscillation in the belief evolution, which implies that neither true state could be learnt correctly by calculating the largest Lyapunov exponents and Hurst exponents.     

Self-organized structures in a superorganism: do ants “behave” like molecules?

While the striking structures (e.g. nest architecture, trail networks) of insect societies may seem familiar to many of us, the understanding of pattern formation still constitutes a challenging problem. Over the last two decades, self-organization has dramatically changed our view on how collective decision-making and structures may emerge out of a population of ant workers having each their own individuality as well as a limited access to information. A variety of collective behaviour spontaneously outcome from multiple interactions between nestmates, even when there is no directing influence imposed by an external template, a pacemaker or a leader. By focussing this review on foraging structures, we show that ant societies display some properties which are usually considered in physico-chemical systems, as typical signatures of self-organization. We detail the key role played by feed-back loops, fluctuations, number of interacting units and sensitivity to environmental factors in the emergence of a structured collective behaviour. Nonetheless, going beyond simple analogies with non-living self-organized patterns, we stress on the specificities of social structures made of complex living units of which the biological features have been selected throughout the evolution depending on their adaptive value. In particular, we consider the ability of each ant individual to process information about environmental and social parameters, to accordingly tune its interactions with nestmates and ultimately to determine the final pattern emerging at the collective level. We emphasize on the parsimony and simplicity of behavioural rules at the individual level which allow an efficient processing of information, energy and matter within the whole colony.     

Stochastic resonance in a model of opinion formation on small-world networks

We analyze the phenomenon of stochastic resonance in an Ising-like system on a small-world network. The system, which is subject to the combined action of noise and an external modulation, can be interpreted as a stylized model of opinion formation by imitation under the effects of a “fashion wave”. Both the amplitude threshold for the detection of the external modulation and the width of the stochastic-resonance peak show considerable variation as the randomness of the underlying small-world network is changed. Received 19 December 2001     

Effective mechanism for social recommendation of news

Recommender systems represent an important tool for news distribution on the Internet. In this work we modify a recently proposed social recommendation model in order to deal with no explicit ratings of users on news. The model consists of a network of users which continually adapts in order to achieve an efficient news traffic. To optimize the network’s topology we propose different stochastic algorithms that are scalable with respect to the network’s size. Agent-based simulations reveal the features and the performance of these algorithms. To overcome the resultant drawbacks of each method we introduce two improved algorithms and show that they can optimize the network’s topology almost as fast and effectively as other not-scalable methods that make use of much more information.     

Influenza epidemic spread simulation for Poland — a large scale, individual based model study

In this work a construction of an agent based model for studying the effects of influenza epidemic in large scale (38 million individuals) stochastic simulations, together with the resulting various scenarios of disease spread in Poland are reported. Simple transportation rules were employed to mimic individuals’ travels in dynamic route-changing schemes, allowing for the infection spread during a journey. Parameter space was checked for stable behaviour, especially towards the effective infection transmission rate variability. Although the model reported here is based on quite simple assumptions, it allowed to observe two different types of epidemic scenarios: characteristic for urban and rural areas. This differentiates it from the results obtained in the analogous studies for the UK or US, where settlement and daily commuting patterns are both substantially different and more diverse. The resulting epidemic scenarios from these ABM simulations were compared with simple, differential equations based, SIR models — both types of the results displaying strong similarities. The pDYN software platform developed here is currently used in the next stage of the project employed to study various epidemic mitigation strategies.     

Video mediated social interaction between groups: System requirements and technology challenges

This paper discusses results from research related to the use of television as a device that supports social interaction between close-knit groups in settings that include more than two locations, each location being potentially equipped with more than one camera. The paper introduces the notion of a framing experience, as a specific scenario or situation within which social communication takes place. It reports on the evaluation of some of the key attributes of social communication through semi-structured interviews, with 16 families across four European countries. The inferences drawn from this study are reduced to four system capabilities including the ability to support: excitement, engagement and entertainment; high quality, reliable audiovisual communications; flexibility and adaptability sufficient to support the unpredictable and reactive nature of human interaction and discourse. These system requirements are, in turn, reduced to a number of technology challenges which if solved will help enable effective social communications between groups, mediated by the television. These technology challenges include: high quality reliable audio visual communication; interaction orchestration, multimedia interpretation and multimedia composition. Finally the paper reflects on the impact the use of framing experiences, such as those described here, could have on strategy and policy for service providers and regulators.     

Social media usage and organizational performance: Reflections of Malaysian social media managers

Social media usage among organizations is growing tremendously. Organizations are now building and maintaining social media public pages to improve their social network salience, enhance interest in their organizations, and build relationships with the online public. The majority of the studies on social media usage are based on the individual perspective while some are from the organizational perspective. However, not many studies have investigated the actual impact of social media usage on organizational performance. Therefore, using the qualitative approach, this study investigates the various purposes of social media usage and its impact on organizational performance. This study however, focuses only on the social media managers’ views. The senior managers of six organizations that are using social media are interviewed from which we find that social media is used for various purposes in organizations, such as advertising and promotion, branding, information search, building customer relations and many more. The results also show that social media has a greater impact on the performance of organizations in terms of enhancement in customer relations and customer service activities, improvement in information accessibility and cost reduction in terms of marketing and customer service.     

Participatory or deliberative democracy? Exploring the mediation effects of perceived online deliberation and online interactive activities on social outcomes

Using the structural equation modeling method (N = 811), this study explores the structural relationships among online news consumption, political participation and social trust, with a focus on the mediating effects of online users’ deliberative perceptions and news-related online interactive activities. The analysis confirms that users’ perceptions of online deliberation exert a significant mediating effect on users’ levels of news consumption, political participation, and social trust. Users’ interactive civic messaging behaviors, on the other hand, solely enhance participatory intentions. The findings also show that the consumption of political news and the consumption of entertainment news have different effects on users’ perceptions of online deliberation, social trust, and political participation. Specifically, while political news has a direct and relatively strong influence on participation, entertainment news has a limited and indirect effect on participation. Online interactive activities are negatively associated with users’ perceived competency for online deliberation. Further implications of the study are also discussed.     

伪影间共性机理驱动的多域感知社交网络深度伪造视频检测

深度伪造技术在社交网络上的滥用引发了人们对视觉内容真实性与可靠性的严重担忧。已有检测算法未充分考虑社交网络上深度伪造视频的退化现象,导致深度伪造检测性能受以压缩为主的伪影信息干扰与上下文相关信息缺失等挑战性问题的限制。压缩编码与深度伪造生成算法上采样操作会在视频上留下伪影,这些伪影可导致真实视频与深度伪造视频间的细粒度差异。该文通过分析压缩伪影与深度伪造伪影的共性机理,揭示了二者间的结构相似性,为深度伪造检测模型抗压缩鲁棒性的增强提供了可靠理论依据。首先,针对压缩噪声对深度伪造特征的干扰,基于压缩伪影与深度伪造伪影频域表示的结构相似性,设计了频域自适应陷波滤波器以消除特定频带上压缩伪影的干扰。其次,为削弱深度伪造检测模型对未知噪声的敏感,设计了基于残差学习的去噪分支。采用基于注意力机制的特征融合方法增强深度伪造判别特征,结合度量学习策略优化网络模型,实现了具有抗压缩鲁棒性的深度伪造检测。理论分析与实验结果表明,与基线方法相比,该文算法在压缩深度伪造视频上的检测性能具有明显提升,并可作为一种即插即用模型与现有检测方法结合以提高其抗压缩鲁棒性。