Dynamics modeling and optimal control for multi-information diffusion in Social Internet of Things

As an ingenious convergence between the Internet of Things and social networks,the Social Internet of Things(SIoT)can provide effective and intelligent information services and has become one of the main platforms for people to spread and share information.Nevertheless,SIoT is characterized by high openness and autonomy,multiple kinds of information can spread rapidly,freely and cooperatively in SIoT,which makes it challenging to accurately reveal the characteristics of the information diffusion process and effectively control its diffusion.To this end,with the aim of exploring multi-information cooperative diffusion processes in SIoT,we first develop a dynamics model for multi-information cooperative diffusion based on the system dynamics theory in this paper.Subsequently,the characteristics and laws of the dynamical evolution process of multi-information cooperative diffusion are theoretically investigated,and the diffusion trend is predicted.On this basis,to further control the multi-information cooperative diffusion process efficiently,we propose two control strategies for information diffusion with control objectives,develop an optimal control system for the multi-information cooperative diffusion process,and propose the corresponding optimal control method.The optimal solution distribution of the control strategy satisfying the control system constraints and the control budget constraints is solved using the optimal control theory.Finally,extensive simulation experiments based on real dataset from Twitter validate the correctness and effectiveness of the proposed model,strategy and method.

Smart object recommendation based on topic learning and joint features in the social internet of things

With the extensive integration of the Internet,social networks and the internet of things,the social internet of things has increasingly become a significant research issue.In the social internet of things application scenario,one of the greatest challenges is how to accurately recommend or match smart objects for users with massive resources.Although a variety of recommendation algorithms have been employed in this field,they ignore the massive text resources in the social internet of things,which can effectively improve the effect of recommendation.In this paper,a smart object recommendation approach named object recommendation based on topic learning and joint features is proposed.The proposed approach extracts and calculates topics and service relevant features of texts related to smart objects and introduces the“thing-thing”relationship information in the internet of things to improve the effect of recommendation.Experiments show that the proposed approach enables higher accuracy compared to the existing recommendation methods.

Set pair three-way overlapping community discovery algorithm for weighted social internet of things

There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is proposed.In the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor nodes.The similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is proposed.According to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is proposed.The nodes are allocated according to the set pair similarity between nodes and different communities.Three-way community structures composed of a positive domain,boundary domain and negative domain are generated iteratively.Next,the overlapping node set is generated according to the calculation results of community node membership.Finally,experiments are carried out on artificial networks and real networks.The results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.

A blockchain-based trustworthy collaborative power trading scheme for 5G-enabled social internet of vehicles

Social Internet of Vehicles(SIoV)falls under the umbrella of social Internet of Things(IoT),where vehicles are socially connected to other vehicles and roadside units that can reliably share information and services with other social entities by leveraging the capabilities of 5G technology,which brings new opportunities and challenges,e.g.,collaborative power trading can address the mileage anxiety of electric vehicles.However,it relies on a trusted central party for scheduling,which introduces performance bottlenecks and cannot be set up in a distributed network,in addition,the lack of transparency in state-of-the-art Vehicle-to-Vehicle(V2V)power trading schemes can introduce further trust issues.In this paper,we propose a blockchain-based trustworthy collaborative power trading scheme for 5G-enabled social vehicular networks that uses a distributed market mechanism to introduce trusted power trading and avoids the dependence on a centralized dispatch center.Based on the game theory,we design the pricing and trading matching mechanism for V2V power trading to obtain maximum social welfare.We use blockchain to record power trading data for trusted pricing and use smart contracts for transaction matching.The simulation results verify the effectiveness of the proposed scheme in improving social welfare and reducing the load on the grid.

The Impact of Internet Usage on Youth Social Interaction in China

The purpose of this paper intends to explore specifically whether heavy usage of the Internet by youths increase or decrease their social interaction opportunities. Issues that will be examined include that of the change of face-to-face communication between the youth and their families, friends and social activities. A quantitative research method with questionnaires is adopted to meet the objective of this study.

Internet and social media usage of orthopaedic patients:A questionnaire-based survey

AIM To evaluate social media usage of orthopaedic patients to search for solutions to their health problems. METHODS The study data were collected using face-to-face questionnaire with randomly selected 1890 patients aged over 18 years who had been admitted to the orthopaedic clinics in different cities and provinces across Turkey. The questionnaire consists of a total of 16 questions pertaining to internet and social media usage and demographics of patients, patients' choice of institution for treatment, patient complaints on admission, online hospital and physician ratings, communication between the patient and the physician and its effects.RESULTS It was found that 34.2%(n = 647) of the participants consulted with an orthopaedist using the internet and 48.7%(n = 315) of them preferred websites that allow users to ask questions to a physician. Of all questionaskers, 48.5%(n = 314) reported having found the answers helpful. Based on the educational level of the participants, there was a highly significant difference between the rates of asking questions to an orthopaedist using the internet(P = 0.001). The rate of questionasking was significantly lower in patients with an elementary education than that in those with secondary, high school and undergraduate education(P = 0.001) The rate of reporting that the answers given was helpful was significantly higher in participants with an undergraduate degree compared to those who were illiterate, those with primary, elementary or high school education(P = 0.001). It was also found that the usage of the internet for health problems was higher among managers-qualified participants than unemployed-housewives, officers, workers-intermediate staff(P < 0.05).CONCLUSION We concluded that patients have been increasingly using the internet and social media to select a specific physician or to seek solution to their health problems in an effective way. Even though the internet and social media offer beneficial effects for physicians or patients, there is still much obscurity regarding their harms and further studies are warranted for necessary arrangements to be made.

Cyber-Physical-Social Based Security Architecture for Future Internet of Things

As the Internet of Things (IoT) is emerging as an attractive paradigm, a typical IoT architecture that U2IoT (Unit IoT and Ubiquitous IoT) model has been presented for the future IoT. Based on the U2IoT model, this paper proposes a cyber-physical-social based security architecture (IPM) to deal with Information, Physical, and Management security perspectives, and presents how the architectural abstractions support U2IoT model. In particular, 1) an information security model is established to describe the mapping relations among U2IoT, security layer, and security requirement, in which social layer and additional intelligence and compatibility properties are infused into IPM;2) physical security referring to the external context and inherent infrastructure are inspired by artificial immune algorithms;3) recommended security strategies are suggested for social management control. The proposed IPM combining the cyber world, physical world and human social provides constructive proposal towards the future IoT security and privacy protection.

A Double-Compensation-Based Federated Learning Scheme for Data Privacy Protection in a Social IoT Scenario

Nowadays,smart wearable devices are used widely in the Social Internet of Things(IoT),which record human physiological data in real time.To protect the data privacy of smart devices,researchers pay more attention to federated learning.Although the data leakage problem is somewhat solved,a new challenge has emerged.Asynchronous federated learning shortens the convergence time,while it has time delay and data heterogeneity problems.Both of the two problems harm the accuracy.To overcome these issues,we propose an asynchronous federated learning scheme based on double compensation to solve the problem of time delay and data heterogeneity problems.The scheme improves the Delay Compensated Asynchronous Stochastic Gradient Descent(DC-ASGD)algorithm based on the second-order Taylor expansion as the delay compensation.It adds the FedProx operator to the objective function as the heterogeneity compensation.Besides,the proposed scheme motivates the federated learning process by adjusting the importance of the participants and the central server.We conduct multiple sets of experiments in both conventional and heterogeneous scenarios.The experimental results show that our scheme improves the accuracy by about 5%while keeping the complexity constant.We can find that our scheme converges more smoothly during training and adapts better in heterogeneous environments through numerical experiments.The proposed double-compensation-based federated learning scheme is highly accurate,flexible in terms of participants and smooth the training process.Hence it is deemed suitable for data privacy protection of smart wearable devices.

Automated Service Search Model for the Social Internet of Things

The social internet of things(SIoT)is one of the emerging paradigms that was proposed to solve the problems of network service discovery,navigability,and service composition.The SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings.In IoT,an object can offer multiple services and different objects can offer the same services with different parameters and interest factors.The proliferation of offered services led to difficulties during service customization and service filtering.This problem is known as service explosion.The selection of suitable service that fits the requirements of applications and objects is a challenging task.To address these issues,we propose an efficient automated query-based service search model based on the local network navigability concept for the SIoT.In the proposed model,objects can use information from their friends or friends of their friends while searching for the desired services,rather than exploring a global network.We employ a centrality metric that computes the degree of importance for each object in the social IoT that helps in selecting neighboring objects with high centrality scores.The distributed nature of our navigation model results in high scalability and short navigation times.We verified the efficacy of our model on a real-world SIoT-related dataset.The experimental results confirm the validity of our model in terms of scalability,navigability,and the desired objects that provide services are determined quickly via the shortest path,which in return improves the service search process in the SIoT.

“摆烂”热词背后青年群体消极社会心态问题研究

“摆烂”一词流行的背后是部分青年群体消极社会心态的表露,其形成原因可归结为社会转型中青年竞争疲倦后习得性无助的加剧,现实困境中青年群体焦虑情绪在网络媒介上的宣泄与传染。“摆烂”一词承载的消极社会心态会消解青年人的奋斗意识和集体意识,影响青年群体参与社会实践的主动性。通过提升青年心理素质、强化主流价值观培育,加强网络空间文化建设和治理,关注青年的刚需问题和心理诉求等治理策略,有助于解决我国青年的心态困境,实现消极社会心态的积极转向,对于社会的良性运转有着积极意义。

互联网使用对老年人社会适应的影响与作用机制

互联网使用对老年人的社会适应产生重要影响,但关于有何影响及如何影响的研究较少,且多数研究聚焦于互联网技术本身,忽视了作为技术使用主体的老年人的“能动性”。基于中国老年社会追踪调查(CLASS2018)数据,参考相关经典理论,发现相比不使用互联网的老年人,使用互联网的老年人的社会适应水平更高,老年人使用互联网的频率越高,其社会适应水平也越高。此外,在互联网使用对老年人社会适应产生影响的过程中,社会参与发挥着正向中介作用。因此,实现积极老龄化不仅需要鼓励老年人主动触网,促进老年人的数字融入、消除数字鸿沟,还要利用互联网不断增进老年人的社会参与。

互联网的思想政治教育功能与社会功能对居民社会公平感的影响:有调节的中介效应模型

本文采用中国综合社会调查(CGSS2017)的数据,选取了18个题项作为研究变量进行研究,以社会信任作为中介变量,社会阶层为调节变量,构建互联网的思想政治教育功能与社会功能对居民社会公平感的影响关系模型。研究结果显示,一是互联网的思想政治教育功能与社会功能对居民社会公平感具有显著的正向影响。二是社会阶层在互联网的思想政治教育功能与社会功能对居民社会公平感的关系中起中介作用。三是社会阶层在社会信任与居民社会公平感的关系中起调节作用,社会阶层负向调节了互联网的思想政治教育功能与社会功能通过社会信任对居民社会公平感的间接效应。该研究不仅揭示了互联网的思想政治教育功能与社会功能对居民社会公平感的作用机制,还具有公共政策价值,即政府关于互联网政策的制定可在提升社会信任和社会阶层的方向拓展,回应居民对社会公平的关切,进而提升居民的社会公平感。

数字乡村建设与农民工就业质量提升

数字乡村建设一方面通过新业态新模式创造出更多更高质量的就业岗位,另一方面通过拓宽信息渠道促进农民工人力资本和社会资本积累,增强农民工在就业市场上的竞争力和议价能力,因而可以赋能农民工高质量就业。将2018年的县域数字乡村指数数据与中国家庭追踪调查(CFPS)数据进行匹配,从客观和主观两个维度综合评价农民工的就业质量,检验数字乡村建设对农民工就业质量的影响,结果表明:数字乡村建设显著提高了农民工就业质量,该结论在内生性处理和一系列稳健性检验中依然成立;数字乡村建设具有显著的信息改善效应,可以通过拓宽信息渠道、促进人岗匹配、增强社会信任等路径来提高农民工的就业质量;数字乡村建设对女性农民工、在婚农民工、中青年农民工、学历较高的农民工和已接入互联网的农民工具有更显著的就业质量提升作用。因此,应加快推进数字乡村建设,充分发挥其各种积极效应,并有效缩小城乡间和农村地区内部的数字鸿沟,促进数字乡村协调发展。

从求助展演、情感共鸣到陌生互助——B站疾病求助类视频评论的情感分析

本文通过爬虫抓取了B站18个疾病求助视频的评论文本,进行文本分析、量化分析和多模态话语分析,探究网友对求助者和视频的支持及社会意义。研究发现,网友对视频众筹给予了充分的情感和工具支持,提供了信息和帮助,而平台算法为求助者提供了技术支持,让视频得以更广泛传播。然而,这种传播也引发了网友对平台和求助内容的质疑,围绕可信度展开了激烈争辩。视频众筹形式依赖平台算法和可见性设计,而非求助者的社交网络。尽管基于利他动机的社会支持有积极价值,但也造成了社会信任问题。

互联网使用与南方稻农耕地质量保护技术采纳--信息搜寻和社会互动的双重视角

近年来极端气候事件频发和国际局势剧烈变化,加剧了我国人地矛盾对国家粮食安全的挑战,加强耕地保护迫在眉睫。而互联网信息技术快速普及成为推进耕地质量保护技术采纳的重要途径。基于有限理性假设和社会互动理论,揭示互联网使用对农户的耕地质量保护技术采纳并不是“万能药”:农户的在线农业信息搜寻显著促进了耕地质量保护技术采纳,但是在线社会互动削弱了在线农业信息搜寻的积极效应;且由于存在“回声室效应”,如果稻农是“非意见领袖”,则上述削弱作用更加明显。本研究为数字农业农村发展中的保护性农业生产技术的应用推广提供了启示。一方面政府应不断强化农村数字基础设施建设并优化农业技术信息的网络治理,以继续促进农户“自下而上”的农业信息获取对技术采纳的积极作用;另一方面,保护性技术的采纳是“科学性”和“本地性”相融合的过程,应进一步鼓励农技研发的本地化并提高农户的数字素养增强其数字信息甄别能力,以克服互联网和社会网络双重互动对技术采纳带来的消极影响。

数字普惠金融促进农村居民创业了吗?——基于互联网支付能力和社会网络双重视角

基于我国2015年、2017年及2019年家庭金融调查数据(CHFS)与数字普惠金融指数,深入探讨数字普惠金融对农村居民创业活动的影响。研究发现:数字普惠金融对农村居民创业具有显著正向影响;数字普惠金融通过互联网支付能力的提升和社会网络传递间接影响农村居民创业;数字普惠金融对中年组农村居民创业的影响更显著,能促进具有低等和中等金融素养水平的农村居民创业,对东部地区农村居民创业具有显著促进作用。

“尔滨”与“小土豆”:旅游地爆红的社会动因及消费深化

哈尔滨成为2024年初的顶流城市,出现现象级的“尔滨与小土豆”景观。究其本质可以发现,第一,一个旅游目的地爆红有社交媒体算法和推送机制的偶然性,但也有深刻的社会原因;成为网红后要想保证游客体验,需要目的地社会的整体性保障作为重要支撑。第二,旅游目的地发展要从资源主体向玩法主体转变,尤其是在现代社会个体越来越陷入“隐身”状态的背景下,要突出社交属性和氛围,满足游客自我表现和凸显主体性的诉求。第三,旅游目的地要吸引消费,就需要回应需求,要站在他者视角来营造“消费圣殿”的空间与环境,处理好消费深化与成本投入之间的平衡,理性看待情绪价值,处理好即时的快感消费与持续的快乐体验之间的关系。

促进还是抑制:互联网使用对老年人主观幸福感的影响研究

依据中国综合社会调查(CGSS 2017)数据,可借以探讨互联网使用对老年人主观幸福感的影响机制,并挖掘社会融合在二者关系间发挥的中介作用。研究发现:互联网社会化使用和非社会化使用对老年人主观幸福感产生正向影响,但影响不显著,对社会融合具有显著的正向影响;社会融合对老年人的主观幸福感具有显著的正向影响;在互联网社会化使用、非社会化使用和老年人主观幸福感之间社会融合起完全中介作用。对于老年人主观幸福感的影响,社会融合是比互联网使用更加重要的因素。基于此,在理论层面,新时期社会治理理论应重视工具理性和情感价值的有机统一,社会支持理论应强调物质支持和情感支持的深度融合;在实践层面,一方面要着力解决老年人智能技术使用困难,另一方面要丰富老年人的社会融合渠道,以此来提升老年人的主观幸福感。

社交媒体对网红城市旅游形象感知影响研究——以山东省淄博市为例

研究选取山东省淄博市作为案例地,搜集新浪微博的网络文本数据,基于“认知—情感”理论模型,利用网络文本分析法分析游客对淄博市的旅游形象感知。结果显示:在认知形象上,主要围绕“淄博烧烤”展开,烧烤已经成为淄博的重要旅游吸引物;在情感形象上,游客感知主要以积极情绪为主,负面情绪较少;从整体形象上来看,淄博市是“网红城市”“烧烤之城”“好客之都”,整体形象良好。对此,淄博市可以挖掘城市特色,推出更具体验性的旅游产品;完善客流监控,引导游客分流;将产品和活动打造成品牌IP,提升影响力;把控市场变化,灵活调整营销策略。