Effects of heterogeneous adoption thresholds on contact-limited social contagions

Limited contact capacity and heterogeneous adoption thresholds have been proven to be two essential characteristics of individuals in natural complex social systems,and their impacts on social contagions exhibit complex nature.With this in mind,a heterogeneous contact-limited threshold model is proposed,which adopts one of four threshold distributions,namely Gaussian distribution,log-normal distribution,exponential distribution and power-law distribution.The heterogeneous edge-based compartmental theory is developed for theoretical analysis,and the calculation methods of the final adoption size and outbreak threshold are given theoretically.Many numerical simulations are performed on the Erdös-Renyi and scale-free networks to study the impact of different forms of the threshold distribution on hierarchical spreading´process,the final adoption size,the outbreak threshold and the phase transition in contact-limited propagation networks.We find that the spreading process of social contagions is divided into three distinct stages.Moreover,different threshold distributions cause different spreading processes,especially for some threshold distributions,there is a change from a discontinuous first-order phase transition to a continuous second-order phase transition.Further,we find that changing the standard deviation of different threshold distributions will cause the final adoption size and outbreak threshold to change,and finally tend to be stable with the increase of standard deviation.

Business Process Analysis and Simulation: The Contact Center of a Public Health and Social Information Office

This article proposes a framework, called BP-M* which includes: 1) a methodology to analyze, engineer, restructure and implement business processes, and 2) a process model that extends the process diagram with the specification of resources that execute the process activities, allocation policies, schedules, times of activities, management of queues in input to the activities and workloads so that the same model can be simulated by a discrete event simulator. The BP-M* framework has been applied to a real case study, a public Contact Center which provides different typologies of answers to users’ requests. The simulation allows to study different system operating scenarios (“What-If” analysis) providing useful information for analysts to evaluate restructuring actions.

Blockchain and IIoT Enabled Solution for Social Distancing and Isolation Management to Prevent Pandemics

Pandemics have always been a nightmare for humanity,especially in developing countries.Forced lockdowns are considered one of the effective ways to deal with spreading such pandemics.Still,developing countries cannot afford such solutions because these may severely damage the country’s econ-omy.Therefore,this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations smoothly.The novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things(IIoT)and blockchain-enabled technologies.Compared to existing studies,the immutable and tamper-proof contact tracing and quarantine management solution is proposed.The use of advanced technologies and information security is a critical area for practitioners in the internet of things(IoT)and corresponding solutions.Therefore,this study also emphasizes information security,end-to-end solution,and experimental results.Firstly,a wearable wristband is proposed,incorporating 4G-enabled ultra-wideband(UWB)technology for smart contact tracing mechanisms in industries to comply with standard operating procedures outlined by the world health organization(WHO).Secondly,distributed ledger technology(DLT)omits the centralized dependency for transmitting contact tracing data.Thirdly,a privacy-preserving tracing mechanism is discussed using a public/private key cryptography-based authentication mechanism.Lastly,based on geofencing techniques,blockchain-enabled machine-to-machine(M2M)technology is proposed for quarantine management.The step-by-step methodology and test results are proposed to ensure contact tracing and quarantine management.Unlike existing research studies,the security aspect is also considered in the realm of blockchain.The practical implementation of the proposed solution also obtains the results.The results indicate the successful implementation of blockchain-enabled contact tracing and isolation management using IoT and geo-fencing techniques,which could help battle pandemic situations.Researchers can also consider the 5G-enabled narrowband internet of things(NB-IoT)technologies to implement contact tracing solutions.

二维面孔识别中族群信息与情绪信息的关系及其影响因素

选取80名藏族学生,采用学习-再认范式,考察二维信息面孔识别中族群信息与情绪信息间的加工关系,以及社会接触程度对这种加工关系的影响。结果显示:(1)对于低社会接触者而言,族群信息与情绪信息加工彼此独立;族群信息加工不受情绪信息影响,存在异族效应;(2)对于高社会接触程度者而言,族群信息加工受情绪信息影响,异族效应出现反转。可见,面孔识别中二维信息的加工关系并非固定不变,考察面孔识别应同时考虑信息的维度和社会接触程度。

数字社交赋能老年群体社会适应机理研究:孤独感应对视角

从孤独感应对视角出发,依据自我决定理论和依恋理论,探究数字社交软件使用对老年群体社会适应感的影响机制。研究发现,情感孤独对老年群体数字社交软件使用意愿具有显著正向影响,而社会孤独的影响不显著;调节应对在孤独感对数字社交软件使用意愿的影响中发挥中介作用,数字社交软件使用意愿正向影响老年群体的主观社会适应感。为帮助老年群体融入数字时代、提升老年群体社会适应感,应从信息服务方面适度提高老年群体网络涉入度、从社会服务方面提高老年群体的网络素养水平、从企业服务方面细分老年群体以满足老年群体差异化需求。

跨地方民族演艺者的社会接触与角色变迁——以佤族艺人为例

旅游演艺在特定时空条件下加剧多元主客文化交往和跨文化互动。我国民族演艺人才逐渐成为旅游劳工移民、少数民族多元社会角色交织的跨地方旅游演艺从业者,其多重的社会接触将有助于阐释旅游情境中的关系复杂性,进一步跳出传统在地性民族旅游演艺研究的范畴。文章选取佤族艺人为案例,以质性研究方法深入探讨旅游情境下跨地方民族演艺者的社会接触特点及其角色变迁。研究发现:跨地方民族演艺者进入旅游情境中,经历了文化交往向职业交往导向叠加的社会接触,加快推进了现代角色多元化进程;同时,旅游情境构建了一个多重社会接触空间,为他们角色管理适应整体社会结构变化提供了缓冲,彰显出从业者主体性视角下旅游情境的社会结构特征。该研究从旅游从业者的视角,为民族文化繁荣如何赋能新时代旅游高质量发展提供有益见解。

APPOW:An Advanced Routing Protocol Based on Parameters Optimization in the Weighted Mobile Social Network

Due to the increasing number of wireless mobile devices,the possibility of mobile communications without infrastructure becomes a reality.The Decentralized Mobile Social Network(DMSN) is a paradigm where nodes can move freely and organize themselves arbitrarily.Routing in these environments is difficult for the reason of the rapid changes of the social relationship graph's topology.Meanwhile,the social ties among nodes change overtime.Therefore,an efficient data forwarding mechanism should be considered over the temporal weighted relationship graph.In this paper,an Advanced routing Protocol based on Parameters Optimization in the Weighted mobile social network(APPOW) is proposed to improve the delivery success ratio and reduce the cost of exchanging information.APPOW combines the normalized relative weights of three local social metrics,i.e.,LinkRank,similarity and contact strength,to select the next relay node.The weights of the three metrics are derived by pair-wise learning algorithm.The result shows that APPOW outperforms the state-ofthe-art SimBet Routing in delivering message and significantly reduces the average hops.Additionally,the delivery performance of APPOW is close to Epidemic Routing but without message duplications.

Social integration: How is it related to self-rated health?

Social integration has well-established health benefits among older adults in observational studies. However, interventions designed to increase social integration have not improved health suggesting important knowledge gaps on how social integration influences health outcomes. This study developed a new measure of social integration, daily social contact, capturing the interpersonal nature of social integration and mobility of individuals, and providing a direct assessment of individuals’ real-time access to companionship and social support. The data used is the 2006-2007 American Time Use Survey (ATUS), which surveyed 25,191 individuals aged 15 years and older (n = 4378 aged 65 years and older). Generalized ordinal logistic regression analyses revealed positive, but non-parallel relationships between daily social contacts and the ordinal categories of self-rated health among older adults. This study may be used to identify populations that experience social exclusion, such that future research can determine more precisely how to intervene to improve health outcomes.

Clustering Indoor Location Data for Social Distancing and Human Mobility to Combat COVID-19

The world is experiencing the unprecedented time of a pandemic caused by the coronavirus disease(i.e.,COVID-19).As a countermeasure,contact tracing and social distancing are essential to prevent the transmission of the virus,which can be achieved using indoor location analytics.Based on the indoor location analytics,the human mobility on a site can be monitored and planned to minimize human’s contact and enforce social distancing to contain the transmission of COVID-19.Given the indoor location data,the clustering can be applied to cluster spatial data,spatio-temporal data and movement behavior features for proximity detection or contact tracing applications.More specifically,we propose the Coherent Moving Cluster(CMC)algorithm for contact tracing,the density-based clustering(DBScan)algorithm for identification of hotspots and the trajectory clustering(TRACLUS)algorithm for clustering indoor trajectories.The feature extraction mechanism is then developed to extract useful and valuable features that can assist the proposed system to construct the network of users based on the similarity of the movement behaviors of the users.The network of users is used to model an optimization problem to manage the human mobility on a site.The objective function is formulated to minimize the probability of contact between the users and the optimization problem is solved using the proposed effective scheduling solution based on OR-Tools.The simulation results show that the proposed indoor location analytics system outperforms the existing clustering methods by about 30%in terms of accuracy of clustering trajectories.By adopting this system for human mobility management,the count of close contacts among the users within a confined area can be reduced by 80%in the scenario where all users are allowed to access the site.

Primary Contacts Identification for COVID-19 Carriers from Surveillance Videos

COVID-19 (Coronavirus disease of 2019) is caused by SARS-CoV2(Severe Acute Respiratory Syndrome Coronavirus 2) and it was first diagnosedin December 2019 in China. As of 25th Aug 2021, there are 165 million con-firmed COVID-19 positive cases and 4.4 million deaths globally. As of today,though there are approved COVID-19 vaccine candidates only 4 billion doseshave been administered. Until 100% of the population is safe, no one is safe. Eventhough these vaccines can provide protection against getting seriously ill anddying from the disease, it does not provide 100% protection from getting infectedand passing it on to others. The more the virus spreads;it has more opportunity tomutate. So, it is mandatory to follow all precautions like maintaining social distance, wearing mask, washing hands frequently irrespective of whether a person isvaccinated or not. To prevent spread of the virus, contact tracing based on socialdistance also becomes equally important. The work proposes a solution that canhelp with contact tracing/identification, knowing the infected persons recent travelhistory (even within the city) for few days before being assessed positive. Whilethe person would be able to give the known contacts with whom he/she has interacted with, he/she will not be aware of who all were in proximity if he/she hadbeen in public places. The proposed solution is to get the CCTV (Closed-CircuitTelevision) video clips from those public places for the specific date and time andidentify the people who were in proximity—i.e., not followed the safe distance tothe infected person. The approach uses YOLO V3 (You Only Look Once) whichuses darknet framework for people detection. Once the infected person is locatedfrom the video frames, the distance from that person to the other people in theframe is found, to check if there is a violation of social distance guideline. If thereis, then the people violating the distance are extracted and identified using Facialdetection and recognition algorithms. Two different solutions for Face detectionand Recognition are implemented and results compared—Dlib based modelsand OpenCV (Open Source Computer Vision Library) based models. The solutions were studied for two different CCTV footages and the results for Dlib basedmodels were better than OpenCV based models for the studied videos.

互联网模式下康复对孤独症儿童社交、发展功能的效果

目的基于互联网模式下观察康复指导训练对孤独症谱系障碍(ASD)儿童社会交往及发展功能的效果。方法选取2021年8月至2022年4月就诊于甘肃省康复中心医院儿童康复科4~6岁ASD儿童60例。根据随机数表法分为对照组(n=30)和观察组(n=30),对照组给予家庭早期干预康复,观察组基于对照组的基础上配合互联网模式下康复指导,3个月为1个观察周期,共2个观察周期(6个月)。采用儿童孤独症评定量表(CARS)、社交反应量表(SRS)、儿童孤独症及相关发育障碍心理教育评定量表(C-PEP-3)测评,对ASD儿童进行康复前,康复3、6个月后评估。结果康复3、6个月后,两组ASD儿童CARS、SRS评分均较康复前低,且观察组低于对照组,差异有统计学意义(P<0.05);康复3、6个月后,两组ASD儿童C-PEP-3评分均较康复前高,且观察组高于对照组,差异有统计学意义(P<0.05)。结论互联网模式下康复指导联合家庭早期干预康复,能够改善ASD儿童社交反应能力及发展功能,提高其生活质量。

中国老年人社会参与和家庭交往对可能肌少症影响的队列研究

目的探讨我国老年人社会参与和家庭交往对可能肌少症发生风险的影响。方法采用队列研究方法,通过握力和重复5次起坐时间测量判断可能肌少症,以“中国健康与养老追踪调查”2011年和2013年收集的5820名非肌少症老年人作为基线数据,随访该队列人群至2015年,采用Cox比例风险模型研究老年人的社会参与和家庭交往与其可能肌少症发生风险的关联。结果与过去1个月未参加个人娱乐活动的老年人相比,参加该类活动的老年人发生可能肌少症的风险降低25%(HR=0.75,95%CI:0.63~0.89,P=0.001);相对于与子女共同居住或交往频繁,与子女交往较频繁和交往不频繁的老年人患可能肌少症风险分别降低18%(HR=0.82,95%CI:0.70~0.95,P=0.011)和30%(HR=0.70,95%CI:0.54~0.90,P=0.006);与没有子女经济支持和未帮助子女照料隔代子女的老年人相比,有子女经济支持、为子女提供隔代照料支持的老年人可能肌少症发生风险分别降低22%(HR=0.78,95%CI:0.69~0.90,P<0.001)和30%(HR=0.70,95%CI:0.60~0.82,P<0.001)。结论我国≥60岁老年人积极参与社交、运动等个人娱乐活动、接受子女经济支持和进行隔代照料可以降低其可能肌少症的发生风险,提升老年人社会和家庭交往水平可以延缓可能肌少症的发生。

《史记》所载周霸事迹考

关于周霸其人其事,最早见于司马迁《史记》,其中《孝武本纪》《封禅书》《卫将军骠骑列传》《儒林列传》等篇章均简略记载了周霸这一人物和其相关事迹。此后,史书对周霸的记载均沿用《史记》中的相关记载,并无增补,以至于周霸其人其事在后世多有未明之处。现遍考《史记》等文献,钩稽分析现存史料,从周霸的仕宦经历、交游情况和学术成就三方面加以论述,以期摸索出周霸相对完整和真实的生平事迹。

一种应对COVID-19疫情的社会接触自动检测方法

由于新冠病毒的高传染性,及早发现患者的密切接触者对于遏制疫情爆发至关重要。而受限于技术发展的水平,目前关于接触检测的方法和研究均需人工参与。提出了一种面向未来的自动化方法,利用加载在感知设备上的移动智能体和边缘协调器在街道上组成多智能体系统,基于对感染者的感知、跟踪和边缘计算,实现了感染者与行人之间的接触概率估算。系列仿真给出了应用部署中的参数比较。仿真结果表明,提出的街道征用模式及边缘计算算法可以进一步改善检测率。

啮齿动物帮助行为动机的实证研究

近年利用啮齿动物模型探究帮助行为动机成为新趋势,共情、减轻自身痛苦和社会接触欲望等被认为是啮齿动物做出帮助行为的动机。本研究以108只Sprague-Dawley大鼠为被试,改进了Carvalheiro等(2019)的帮助行为实验装置,以三个实验探究啮齿动物帮助行为的主要动机。研究结果表明:(1)不论暗室是否存在,社会接触欲望和追求有趣环境是帮助行为的主要动机;(2)自身痛苦的减轻以及之前的社会接触经历而非受困经历有助于帮助行为的发生及持续性;(3)共情或许并非帮助行为的主要动机,而是对帮助行为过程的描述。

青年亚文化视角下的青年文化认同建构——以熊猫头表情包为例

熊猫头表情包是当代青年在进行互联网社交时重要的社交工具,是青年亚文化的重要体现之一。它因网友对于不同元素的拼贴(比如熊猫头元素和人的面部表情的组合)而诞生,表现出明显的同构性,在一次次全民狂欢中传播,背后体现的是当代青年在进行网络社交时所具备的高度的圈内认同与明显的社交边界感。熊猫头表情包对于了解青年亚文化非常重要。该文对熊猫头表情包的拼贴组成、传播方式进行了研究,旨在更好地认识当代青年在互联网社交中的自我定位,理解当代年轻人对于自身个性的独特表达方式,加深对青年群体进行互联网社交现实需要的相关认识,从而把握青年网络社交认同与克制并存的特点。

社会距离视角下我国对东盟地区的国际传播效果研究——基于外群威胁的调节效应分析

媒体渠道是推动国家间心相近、民相亲进而带动其他领域深入发展的重要途径。本文采用OCEES数据库,在群际接触理论框架下,借助群体关系研究中的社会距离量表对我国在东盟地区的国际传播效果展开研究。研究结果显示,本国社交媒体使用、中国传统媒体使用和中国社交媒体使用均能够显著拉进当地民众与中国人之间的社会距离,其中对社会距离预测能力最强的变量是本国社交媒体使用,其次是中国社交媒体使用。外群威胁对本国社交媒体使用与社会距离之间的关系产生了调节作用。

在线学习社交行为对学习效果影响的实证研究

目前在线学习过程中流行社交化学习,学习的环境、教学模式、教学载体等都发生了深刻的变化,在线学习的教师、技术平台、学生、知识传播、认知等形成互相关联的关系网络,这将对在线学习的学习效果产生质的影响。因此,通过假设论证和调研,基于结构方程(SEM)分析出在线学习过程中社交对其学习效果的影响因素。研究发现,在线学习者社交行为几个维度中的参与度、分享、信任与认知对学习效果起到直接的影响作用,网络关系、社交性学习动机间接地对学习效果起到影响作用。

群际威胁:影响因素与减少策略

群际威胁是增强消极刻板印象和偏见的重要因素,甚至可以导致群际冲突或暴力。影响群际威胁的因素包括个体的感知与经验、群体特征、社会政策和法规等。通过改变社会分类,模糊群际边界,并创造群际接触的机会,能够增加群际认同感,降低群际威胁感,减少群际偏见,促进积极的群际关系。今后的研究需在不同的社会环境中完善群际威胁的理论模型,并探索相关变量相互作用的内在机制,为促进和改善群际关系提供理论依据。

群际信任的增进:社会认同与群际接触的方法

群际信任是衡量群际关系的一个重要尺度。群际信任指人们在群际互动中对其他群体成员的行为或意向做积极预期而且愿意承受相应的风险,这种信任主要是由群体成员所属的社会身份所决定的,表现为内群体成员对外群体成员的信任。影响群际信任的因素包括社会群体身份及其表征和群体之间的接触经验,增进群际信任的方法主要包括社会认同与群际接触两大类方法。未来的研究需结合已有进展和社会现实问题对中国的群际信任问题及增进方法进行深入和系统的探讨。