基于严格可控理论的社交网络信息传播控制方法

社交网络信息传播控制通过在合适的时机选择最佳的控制点,以较小的代价实现对大部分甚至整个网络的信息传播控制。社交网络用户间的弱关系往往具有信息需求互补、行为取向不断同化的特点,使其在信息扩散过程中有着不可忽视甚至爆发式的传播作用。针对这一问题,考虑社交网络强弱关系对信息传播的影响,该文提出一种基于严格可控理论的信息传播控制方法。首先,针对强关系对信息传播的影响,提取用户间的亲密度、权威性以及互动频率3个影响因素,构建强度关系网络。其次,考虑到信息传播中的弱关系特性,对网络中具有潜在价值的弱关系进行识别,并对强度关系网络中的连边权值加以更新。最后,利用严格可控理论找出网络中的驱动节点组,并根据信息传播的特征选取驱动节点集,对信息传播进行控制。实验结果表明,该文所提传播控制方法能对信息传播的促进或抑制进行有效控制,为社交网络信息传播控制提供新的方法和思路。     

融合多权重因素的低秩概率矩阵分解推荐模型

针对个性化推荐精度较低、对冷启动敏感等问题,该文提出一种融合多权重因素的低秩概率矩阵分解推荐模型MWFPMF。模型利用给定的社交网络构建信任网络,借助Page rank算法和信任传递机制求取用户间信任度;基于Page rank计算用户社会地位,利用活动评分和评分时间修正用户间关系权重;引入词频-逆文本频率技术(TF-IDF)求取用户标签,通过标签相似性表征用户间同质性;将用户间信任度、用户社会地位影响力和用户同质性3因素融入低秩概率矩阵分解中,从而使用户偏好和活动特征映射到同一低秩空间,实现用户-活动评分矩阵的分解,在正则化约束下,最终完成低秩特征矩阵对用户评分缺失的有效预测。利用豆瓣同城北京和Ciao数据集确定各模块的参数设置值。通过仿真对比实验可知,本推荐模型获得了较高的推荐精度,与其他5种传统推荐算法相比,平均绝对误差至少降低了6.58%,均方差误差至少降低了6.27%,与深度学习推进算法相比,推荐精度基本接近;在冷启动用户推荐上优势明显,与其他推荐算法相比,平均绝对误差至少降低了0.89%,均方差误差至少降低了3.01%。     

Association between Social Frailty and Sleep Quality among Community-dwelling Older Adults: A Cross-sectional Study

Objective: We examined the association between social frailty and subjective sleep quality among community-dwelling adults. Methods: This cross-sectional study recruited Japanese adults over the age of 60 years from health check-ups held in a public townhall in a suburban area between 2018 and 2019. Social frailty was evaluated using five criteria (living alone, not visiting friends sometimes, going out less frequently than the last year, not feeling helpful to friends or family, and not talking to someone every day) and categorized into three groups: non-frailty, pre-frailty, and frailty. Sleep quality was assessed according to the Pittsburgh Sleep Quality Index (PSQI) by giving participants a self-reported questionnaire. We performed multivariable linear regression analysis, denoting social frailty as an independent variable, and the global PSQI score as a dependent variable. Results: Data from 300 older adults were analyzed, 51.0% of whom were female. The participants'' mean age was 73.0 years (standard deviation = 5.8). Multivariable analysis revealed the notable association between social frailty and a high global PSQI score (compared with non-frailty, frailty: β = 0.94, 95% CI = 0.08 to 1.80, p = 0.033). Of the five determiners of social frailty, not talking with someone every day was especially associated with a high global PSQI score (β = 1.57, 95% CI = 0.49 to 2.66, p = 0.005). Conclusion: The present study suggests that social frailty is associated with poor sleep quality among community-dwelling older adults. Our findings indicate the importance of social frailty on sleep quality among older adults.     

Limited resolution in complex network community detection with Potts model approach

According to Fortunato and Barthélemy, modularity-based community detection algorithms have a resolution threshold such that small communities in a large network are invisible. Here we generalize their work and show that the q-state Potts community detection method introduced by Reichardt and Bornholdt also has a resolution threshold. The model contains a parameter by which this threshold can be tuned, but no a priori principle is known to select the proper value. Single global optimization criteria do not seem capable for detecting all communities if their size distribution is broad.     

SPETA: Social pervasive e-Tourism advisor

Tourism is one of the major sources of income for many countries. Therefore, providing efficient, real-time service for tourists is a crucial competitive asset which needs to be enhanced using major technological advances. The current research has the objective of integrating technological innovation into an information system, in order to build a better user experience for the tourist. The principal strength of the approach is the fusion of context-aware pervasive systems, GIS systems, social networks and semantics. This paper presents the SPETA system, which uses knowledge of the user’s current location, preferences, as well as a history of past locations, in order to provide the type of recommender services that tourists expect from a real tour guide.     

Random field Ising model and community structure in complex networks

We propose a method to determine the community structure of a complex network. In this method the ground state problem of a ferromagnetic random field Ising model is considered on the network with the magnetic field B_s = +∞, B_t = -∞, and B_i≠s,t=0 for a node pair s and t. The ground state problem is equivalent to the so-called maximum flow problem, which can be solved exactly numerically with the help of a combinatorial optimization algorithm. The community structure is then identified from the ground state Ising spin domains for all pairs of s and t. Our method provides a criterion for the existence of the community structure, and is applicable equally well to unweighted and weighted networks. We demonstrate the performance of the method by applying it to the Barabási-Albert network, Zachary karate club network, the scientific collaboration network, and the stock price correlation network. (Ising, Potts, etc.)     

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.     

含社会地位的随机内生经济增长模型

本文在考虑产出波动的前提下,将个人的社会地位纳入消费者的效用函数,建立连续时间内的随机内生经济增长模型,利用随机最优化方法,分析随机波动和个人资本存量的变化对经济增长的影响.     

Characterization of rankings generated by linear discriminant analysis

Pairwise linear discriminant analysis can be regarded as a process to generate rankings of the populations. But in general, not all rankings are generated. We give a characterization of generated rankings. We also derive some basic properties of this model.     

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