The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlatio...The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.展开更多
Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims ...Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims to validate the 21-item SocialNetwork Addiction Scale-Chinese(SNAS-C)in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population.Methods:A crosssectional survey was conducted,recruiting 3387 college students.Latent profile analysis(LPA)and receiver operating characteristic(ROC)curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C.Results:Three profile models were selected based on multiple statistical criteria,classifying participants into low-risk,moderate-risk,and high-risk groups.The highest-risk group was defined as“positive”for SNA,while the remaining groups were considered“negative”,serving as the reference standard for ROC analysis.The optimal cutoff score was determined to be 72(sensitivity:98.2%,specificity:96.86%),with an overall classification accuracy of 97.0%.The“positive”group reported significantly higher frequency of social network usage,greater digitalmedia dependence scores,and a higher incidence of network addiction.Conclusion:This study identified the optimal cutoff score for the SNAS-C as≥72,demonstrating high sensitivity,specificity,and diagnostic accuracy.This threshold effectively distinguishes between high-risk and low-risk SNA.展开更多
Personalized search utilizes user preferences to optimize search results,and most existing studies obtain user preferences by analyzing user behaviors in search engines that provide click-through data.However,the beha...Personalized search utilizes user preferences to optimize search results,and most existing studies obtain user preferences by analyzing user behaviors in search engines that provide click-through data.However,the behavioral data are noisy because users often clicked some irrelevant documents to find their required information,and the new user cold start issue represents a serious problem,greatly reducing the performance of personalized search.This paper attempts to utilize online social network data to obtain user preferences that can be used to personalize search results,mine the knowledge of user interests,user influence and user relationships from online social networks,and use this knowledge to optimize the results returned by search engines.The proposed model is based on a holonic multiagent system that improves the adaptability and scalability of the model.The experimental results show that utilizing online social network data to implement personalized search is feasible and that online social network data are significant for personalized search.展开更多
The Internet of thing(Io T)emerges as a possible solution to realize a smart life in the modern age.In this article,we design and realize a novel near field communication(NFC)-driven smart home system for Io T,which i...The Internet of thing(Io T)emerges as a possible solution to realize a smart life in the modern age.In this article,we design and realize a novel near field communication(NFC)-driven smart home system for Io T,which integrates the wireless sensor network(WSN),social networks,and the cloud computing.NFC technology provides a way for users to exchange information between them and the system by simply contacting.So,we propose to use NFC as the system drive in the architecture,such that users can intuitively interact with the system and deliver their intentions.Then,the corresponding service over the system will control or adjust the“things”at home to fit users'needs.Furthermore,the proposed system provides a platform for developers to easily and rapidly implement their smart home related services.In the system,WSN sensing and control,NFC communications and identification,user profile management and preference analysis,and social network integration are all provided as platform services.We will show how the system works for home automation,intruder detection,and social network sharing.展开更多
Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communica...Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.展开更多
The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children a...The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.展开更多
Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.How...Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.However,more research is needed to identify the factors driving cryptocurrency adoption and understand its impact.We use social network analysis(SNA)to identify the influencing factors and reveal the impact of each on cryptocurrency adoption.Our analysis initially revealed 44 influential factors,which were later reduced to 25 factors,each exerting a different influence.Based on the SNA,we classify these factors into highly,moderately,and least influential categories.Discomfort and optimism are the most influential determinants of adoption.Moderately influential factors include trust,risk,relative advantage,social influence,and perceived behavioral control.Price/value,facilitating conditions,compatibility,and usefulness are the least influential.The factors affecting cryptocurrency adoption are interdependent.Our findings can help policymakers understand the factors influencing cryptocurrency adoption and aid in developing appropriate legal frameworks for cryptocurrency use.展开更多
Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and acc...Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.展开更多
Social networks are vital for building the livelihood resilience of rural households.However,the impact of social networks on rural household livelihood resilience remains em-pirically underexplored,and most existing ...Social networks are vital for building the livelihood resilience of rural households.However,the impact of social networks on rural household livelihood resilience remains em-pirically underexplored,and most existing studies do not disaggregate social networks into different dimensions,which limits the understanding of specific mechanisms.Based on 895 household samples collected in China's Dabie Mountains and structural equation modeling,this paper explored the pathway to enhance livelihood resilience through social networks by dis-aggregating it into five dimensions:network size,interaction intensity,social cohesion,social support,and social learning.The results indicate that:(1)Livelihood assets,adaptive capacity and safety nets significantly contribute to livelihood resilience,whereas sensitivity negatively affects it.Accessibility to basic services has no significant relationship with livelihood resilience in the study area.(2)Social networks and their five dimensions positively impact livelihood re-silience,with network support having the greatest impact.Therefore,both the government and rural households should recognize and enhance the role of social networks in improving liveli-hood resilience under frequent disturbances.These findings have valuable implications for mitigating the risks of poverty recurrence and contributing to rural revitalization.展开更多
Dynamic publishing of social network graphs offers insights into user behavior but brings privacy risks, notably re-identification attacks on evolving data snapshots. Existing methods based on -anonymity can mitigate ...Dynamic publishing of social network graphs offers insights into user behavior but brings privacy risks, notably re-identification attacks on evolving data snapshots. Existing methods based on -anonymity can mitigate these attacks but are cumbersome, neglect dynamic protection of community structure, and lack precise utility measures. To address these challenges, we present a dynamic social network graph anonymity scheme with community structure protection (DSNGA-CSP), which achieves the dynamic anonymization process by incorporating community detection. First, DSNGA-CSP categorizes communities of the original graph into three types at each timestamp, and only partitions community subgraphs for a specific category at each updated timestamp. Then, DSNGA-CSP achieves intra-community and inter-community anonymization separately to retain more of the community structure of the original graph at each timestamp. It anonymizes community subgraphs by the proposed novel -composition method and anonymizes inter-community edges by edge isomorphism. Finally, a novel information loss metric is introduced in DSNGA-CSP to precisely capture the utility of the anonymized graph through original information preservation and anonymous information changes. Extensive experiments conducted on five real-world datasets demonstrate that DSNGA-CSP consistently outperforms existing methods, providing a more effective balance between privacy and utility. Specifically, DSNGA-CSP shows an average utility improvement of approximately 30% compared to TAKG and CTKGA for three dynamic graph datasets, according to the proposed information loss metric IL.展开更多
Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 ...Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 during concurrent outbreaks in Marburg and Frankfurt,Germany,and in Belgrade,Serbia,linked to laboratory use of African green monkeys imported from Uganda.Subsequent outbreaks and isolated cases have been reported in various African countries,including Angola,the Democratic Republic of the Congo,Equatorial Guinea,Ghana,Guinea,Kenya,Rwanda,South Africa(in an individual with recent travel to Zimbabwe),Tanzania,and Uganda.Initial human MVD infections typically occur due to prolonged exposure to mines or caves inhabited by Rousettus aegyptiacus fruit bats,the natural hosts of the virus.展开更多
This paper aims to introduce the novel concept of neutrosophic crisp soft set(NCSS),including various types of neutrosophic crisp soft sets(NCSSs)and their fundamental operations.We define NCS-mapping and its inverse ...This paper aims to introduce the novel concept of neutrosophic crisp soft set(NCSS),including various types of neutrosophic crisp soft sets(NCSSs)and their fundamental operations.We define NCS-mapping and its inverse NCS-mapping between two NCS-classes.We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems(SNSs)for our various generations.We investigate the advantages,disadvantages,and natural aspects of SNSs for five generations.With the changing of the generations,it is analyzed that emerging trends and the benefits of SNSs are increasing day by day.The suggested modeling with NCS-mapping is applicable in solving various decision-making problems.展开更多
A number of mobile Online Social Networking （OSN） services have appeared in the market in recent times. While most mobile systems benefit greatly from cloud services, centralized servers and communications infrastru...A number of mobile Online Social Networking （OSN） services have appeared in the market in recent times. While most mobile systems benefit greatly from cloud services, centralized servers and communications infrastructure is not always available. Nor are location-based services offered to mobile devices without GPS. To take advantage of cloud and to address these problems, a Wi-Fi based multihop networking system called MoNet is proposed. On top of MONET we propose a privacy-aware geosocial networking service called WiFace. Where there is no infrastructure, a distributed content sharing protocol significantly shortens the relay path, reduces conflicts, and improves data availability. Furthermore, a security mechanism is developed to protect privacy. Comprehensive experiments performed on MoNet show that the system is more than sufficient to support social networking and even audio and video applications.展开更多
To discover and identify the influential nodes in any complex network has been an important issue.It is a significant factor in order to control over the network.Through control on a network,any information can be spr...To discover and identify the influential nodes in any complex network has been an important issue.It is a significant factor in order to control over the network.Through control on a network,any information can be spread and stopped in a short span of time.Both targets can be achieved,since network of information can be extended and as well destroyed.So,information spread and community formation have become one of the most crucial issues in the world of SNA(Social Network Analysis).In this work,the complex network of twitter social network has been formalized and results are analyzed.For this purpose,different network metrics have been utilized.Visualization of the network is provided in its original form and then filter out(different percentages)from the network to eliminate the less impacting nodes and edges for better analysis.This network is analyzed according to different centrality measures,like edge-betweenness,betweenness centrality,closeness centrality and eigenvector centrality.Influential nodes are detected and their impact is observed on the network.The communities are analyzed in terms of network coverage considering theMinimum Spanning Tree,shortest path distribution and network diameter.It is found that these are the very effective ways to find influential and central nodes from such big social networks like Facebook,Instagram,Twitter,LinkedIn,etc.展开更多
Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may r...Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.展开更多
[Objective] To analyze the key factor in agricultural technology diffusion- technology support, and to explore the method to quicken the diffusion of agricultural technology. [Method] The technology acquisition advant...[Objective] To analyze the key factor in agricultural technology diffusion- technology support, and to explore the method to quicken the diffusion of agricultural technology. [Method] The technology acquisition advantage of social network was il- lustrated by summarizing the status and characteristics of agricultural technology and technology supporting types in the process of agriculture technology diffusion. [Result] The multi-layer, complex, persistence, systematization features of agricultural technol- ogy require support and help of technology from surrounding social network to ulti- mately internalize the technology. [Conclusion] Using social networks for the technol- ogy support will be a powerful supplement to the system of agricultural technology diffusion.展开更多
Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We...Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We used a joint network model- ing approach to examine the interdependencies between two behavioral networks, aggression and status signaling, from four sta- ble and three unstable groups of rhesus macaques in order to identify characteristic patterns of network interdependence in stable groups that are readily distinguishable from unstable groups. Our results showed that the most prominent source of aggres- sion-status network interdependence in stable social groups came from more frequent dyads than expected with opposite direc- tion status-aggression （i.e. A threatens B and B signals acceptance of subordinate status）. In contrast, unstable groups showed a decrease in opposite direction aggression-status dyads （but remained higher than expected） as well as more frequent than ex- pected dyads with bidirectional aggression. These results demonstrate that not only was the stable joint relationship between ag- gression and status networks readily distinguishable from unstable time points, social instability manifested in at least two differ- ent ways. In sum, our joint modeling approach may prove useful in quantifying and monitoring the complex social dynamics of any wild or captive social system, as all social systems are composed of multiple interconnected networks [Current Zoology 61 （1）： 70-84, 2015].展开更多
Invasive alien pest insect species represent a major threat for agriculture and biodiversity. Because chemical treatments employed to contrast such pests elicit serious environmental and human health problems, a great...Invasive alien pest insect species represent a major threat for agriculture and biodiversity. Because chemical treatments employed to contrast such pests elicit serious environmental and human health problems, a great effort is currently directed to develop long term and environmentally friendly biological control strategies. However, the successful application of some promising techniques, such as the Sterile Insect Technique （SIT）, requires a deep knowledge of the pest basic biology. Here, we argue that understanding pest sexual biology using a social network approach can significantly improve the performance of con- trol strategies. For example, SIT may benefit from understanding how individuals interact and how males accede to reproduction, in order to target the most reproductively active and polygamic males. In this paper we studied the socio-sexual networks of the Asian red palm weevil （RPW） Rhynchophorusferrugineus, a worldwide invader which is causing heavy economic impacts on several palm species. We found that the RPW has a highly promiscuous mating system, characterized by forced interruptions of pair copulations by additional males. The social network is highly non-random nor regular： few males almost monopolize repro- duction, behaving as key-players in the network of matings. Additionally, males have a stable pattern of sexual behaviour over time. We use RPW social network as a case study to direct the development of management techniques such as SIT strategy [Current Zoology 61 （1）： 85-97, 2015].展开更多
In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behav...In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behavior of individuals, and we define and quantify these factors. We consider these factors as characteristic attributes and use a Bayesian classifier to classify individuals. Considering the forwarding delay characteristics of information dissemination, we present a random time generation method that simulates the delay of information dissemination. Given time and other constraints, a user might not look at all the information that his/her friends published. Therefore, this paper proposes an algorithm to predict information visibility, i.e., it estimates the probability that an individual will see the information. Based on the classification of individual behavior and combined with our random time generation and information visibility prediction method, we propose an information dissemination model based on individual behavior. The model can be used to predict the scale and speed of information propagation. We use data sets from Sina Weibo to validate and analyze the prediction methods of the individual behavior and information dissemination model based on individual behavior. A previously proposedinformation dissemination model provides the foundation for a subsequent study on the evolution of the network and social network analysis. Predicting the scale and speed of information dissemination can also be used for public opinion monitoring.展开更多
Online social networks have gradually permeated into every aspect of people's life.As a research hotspot in social network, user influence is of theoretical and practical significant for information transmission, ...Online social networks have gradually permeated into every aspect of people's life.As a research hotspot in social network, user influence is of theoretical and practical significant for information transmission, optimization and integration. A prominent application is a viral marketing campaign which aims to use a small number of targeted infl uence users to initiate cascades of infl uence that create a global increase in product adoption. In this paper, we analyze mainly evaluation methods of user infl uence based on IDM evaluation model, Page Rank evaluation model, use behavior model and some other popular influence evaluation models in currently social network. And then, we extract the core idea of these models to build our influence evaluation model from two aspects, relationship and activity. Finally, the proposed approach was validated on real world datasets,and the result of experiments shows that our method is both effective and stable.展开更多
文摘The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.
基金supported by the National Natural Science Foundation of China(Grant No.72364006).
文摘Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims to validate the 21-item SocialNetwork Addiction Scale-Chinese(SNAS-C)in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population.Methods:A crosssectional survey was conducted,recruiting 3387 college students.Latent profile analysis(LPA)and receiver operating characteristic(ROC)curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C.Results:Three profile models were selected based on multiple statistical criteria,classifying participants into low-risk,moderate-risk,and high-risk groups.The highest-risk group was defined as“positive”for SNA,while the remaining groups were considered“negative”,serving as the reference standard for ROC analysis.The optimal cutoff score was determined to be 72(sensitivity:98.2%,specificity:96.86%),with an overall classification accuracy of 97.0%.The“positive”group reported significantly higher frequency of social network usage,greater digitalmedia dependence scores,and a higher incidence of network addiction.Conclusion:This study identified the optimal cutoff score for the SNAS-C as≥72,demonstrating high sensitivity,specificity,and diagnostic accuracy.This threshold effectively distinguishes between high-risk and low-risk SNA.
基金supported by the National Natural Science Foundation of China (61972300, 61672401, 61373045, and 61902288,)the Pre-Research Project of the “Thirteenth Five-Year-Plan” of China (315***10101 and 315**0102)
文摘Personalized search utilizes user preferences to optimize search results,and most existing studies obtain user preferences by analyzing user behaviors in search engines that provide click-through data.However,the behavioral data are noisy because users often clicked some irrelevant documents to find their required information,and the new user cold start issue represents a serious problem,greatly reducing the performance of personalized search.This paper attempts to utilize online social network data to obtain user preferences that can be used to personalize search results,mine the knowledge of user interests,user influence and user relationships from online social networks,and use this knowledge to optimize the results returned by search engines.The proposed model is based on a holonic multiagent system that improves the adaptability and scalability of the model.The experimental results show that utilizing online social network data to implement personalized search is feasible and that online social network data are significant for personalized search.
基金supported in part by the NSC under Grant No.103-2815-C-024-013-E and 102-2218-E-009-014-MY3the MOST under Grant No.103-2221-E-024-005
文摘The Internet of thing(Io T)emerges as a possible solution to realize a smart life in the modern age.In this article,we design and realize a novel near field communication(NFC)-driven smart home system for Io T,which integrates the wireless sensor network(WSN),social networks,and the cloud computing.NFC technology provides a way for users to exchange information between them and the system by simply contacting.So,we propose to use NFC as the system drive in the architecture,such that users can intuitively interact with the system and deliver their intentions.Then,the corresponding service over the system will control or adjust the“things”at home to fit users'needs.Furthermore,the proposed system provides a platform for developers to easily and rapidly implement their smart home related services.In the system,WSN sensing and control,NFC communications and identification,user profile management and preference analysis,and social network integration are all provided as platform services.We will show how the system works for home automation,intruder detection,and social network sharing.
基金MKE(the Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1121-0010)
文摘Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.
基金supported by the IITP(Institute of Information&Communications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korean government(Ministry of Science and ICT)(IITP-2025-RS-2024-00438056).
文摘The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.
文摘Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.However,more research is needed to identify the factors driving cryptocurrency adoption and understand its impact.We use social network analysis(SNA)to identify the influencing factors and reveal the impact of each on cryptocurrency adoption.Our analysis initially revealed 44 influential factors,which were later reduced to 25 factors,each exerting a different influence.Based on the SNA,we classify these factors into highly,moderately,and least influential categories.Discomfort and optimism are the most influential determinants of adoption.Moderately influential factors include trust,risk,relative advantage,social influence,and perceived behavioral control.Price/value,facilitating conditions,compatibility,and usefulness are the least influential.The factors affecting cryptocurrency adoption are interdependent.Our findings can help policymakers understand the factors influencing cryptocurrency adoption and aid in developing appropriate legal frameworks for cryptocurrency use.
基金Fundação de AmparoàPesquisa do Estado da Bahia(FAPESB),Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico(CNPq)organizations for supporting the Graduate Program in Computer Science at the Federal University of Bahia.
文摘Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.
基金National Natural Science Foundation of China,No.42371315,No.41901213。
文摘Social networks are vital for building the livelihood resilience of rural households.However,the impact of social networks on rural household livelihood resilience remains em-pirically underexplored,and most existing studies do not disaggregate social networks into different dimensions,which limits the understanding of specific mechanisms.Based on 895 household samples collected in China's Dabie Mountains and structural equation modeling,this paper explored the pathway to enhance livelihood resilience through social networks by dis-aggregating it into five dimensions:network size,interaction intensity,social cohesion,social support,and social learning.The results indicate that:(1)Livelihood assets,adaptive capacity and safety nets significantly contribute to livelihood resilience,whereas sensitivity negatively affects it.Accessibility to basic services has no significant relationship with livelihood resilience in the study area.(2)Social networks and their five dimensions positively impact livelihood re-silience,with network support having the greatest impact.Therefore,both the government and rural households should recognize and enhance the role of social networks in improving liveli-hood resilience under frequent disturbances.These findings have valuable implications for mitigating the risks of poverty recurrence and contributing to rural revitalization.
基金supported by the Natural Science Foundation of China(No.U22A2099)the Innovation Project of Guangxi Graduate Education(YCBZ2023130).
文摘Dynamic publishing of social network graphs offers insights into user behavior but brings privacy risks, notably re-identification attacks on evolving data snapshots. Existing methods based on -anonymity can mitigate these attacks but are cumbersome, neglect dynamic protection of community structure, and lack precise utility measures. To address these challenges, we present a dynamic social network graph anonymity scheme with community structure protection (DSNGA-CSP), which achieves the dynamic anonymization process by incorporating community detection. First, DSNGA-CSP categorizes communities of the original graph into three types at each timestamp, and only partitions community subgraphs for a specific category at each updated timestamp. Then, DSNGA-CSP achieves intra-community and inter-community anonymization separately to retain more of the community structure of the original graph at each timestamp. It anonymizes community subgraphs by the proposed novel -composition method and anonymizes inter-community edges by edge isomorphism. Finally, a novel information loss metric is introduced in DSNGA-CSP to precisely capture the utility of the anonymized graph through original information preservation and anonymous information changes. Extensive experiments conducted on five real-world datasets demonstrate that DSNGA-CSP consistently outperforms existing methods, providing a more effective balance between privacy and utility. Specifically, DSNGA-CSP shows an average utility improvement of approximately 30% compared to TAKG and CTKGA for three dynamic graph datasets, according to the proposed information loss metric IL.
文摘Marburg virus disease(MVD)is a highly fatal illness,with a case fatality rate of up to 88%,though this rate can be significantly reduced with prompt and effective patient care.The disease was first identified in 1967 during concurrent outbreaks in Marburg and Frankfurt,Germany,and in Belgrade,Serbia,linked to laboratory use of African green monkeys imported from Uganda.Subsequent outbreaks and isolated cases have been reported in various African countries,including Angola,the Democratic Republic of the Congo,Equatorial Guinea,Ghana,Guinea,Kenya,Rwanda,South Africa(in an individual with recent travel to Zimbabwe),Tanzania,and Uganda.Initial human MVD infections typically occur due to prolonged exposure to mines or caves inhabited by Rousettus aegyptiacus fruit bats,the natural hosts of the virus.
基金the Deanship of Scientific Research at King Khalid University for funding this work through General Research Project under Grant No.R.G.P.2/181/44.
文摘This paper aims to introduce the novel concept of neutrosophic crisp soft set(NCSS),including various types of neutrosophic crisp soft sets(NCSSs)and their fundamental operations.We define NCS-mapping and its inverse NCS-mapping between two NCS-classes.We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems(SNSs)for our various generations.We investigate the advantages,disadvantages,and natural aspects of SNSs for five generations.With the changing of the generations,it is analyzed that emerging trends and the benefits of SNSs are increasing day by day.The suggested modeling with NCS-mapping is applicable in solving various decision-making problems.
基金supported by National Natural Science Foundation of China under Grant No. 90818021, and 9071803National Natural Science Foundation of China under Grant No. 60828003+3 种基金supported by Tsinghua National Laboratory for Information Science and Technology(TNList)NSF CNS0832120National Basic Research Program of China ("973"Program) under grant No. 2010CB328100the National High Technology Research and Development Program of China ("863"Program) under grant No. 2007AA01Z180
文摘A number of mobile Online Social Networking （OSN） services have appeared in the market in recent times. While most mobile systems benefit greatly from cloud services, centralized servers and communications infrastructure is not always available. Nor are location-based services offered to mobile devices without GPS. To take advantage of cloud and to address these problems, a Wi-Fi based multihop networking system called MoNet is proposed. On top of MONET we propose a privacy-aware geosocial networking service called WiFace. Where there is no infrastructure, a distributed content sharing protocol significantly shortens the relay path, reduces conflicts, and improves data availability. Furthermore, a security mechanism is developed to protect privacy. Comprehensive experiments performed on MoNet show that the system is more than sufficient to support social networking and even audio and video applications.
文摘To discover and identify the influential nodes in any complex network has been an important issue.It is a significant factor in order to control over the network.Through control on a network,any information can be spread and stopped in a short span of time.Both targets can be achieved,since network of information can be extended and as well destroyed.So,information spread and community formation have become one of the most crucial issues in the world of SNA(Social Network Analysis).In this work,the complex network of twitter social network has been formalized and results are analyzed.For this purpose,different network metrics have been utilized.Visualization of the network is provided in its original form and then filter out(different percentages)from the network to eliminate the less impacting nodes and edges for better analysis.This network is analyzed according to different centrality measures,like edge-betweenness,betweenness centrality,closeness centrality and eigenvector centrality.Influential nodes are detected and their impact is observed on the network.The communities are analyzed in terms of network coverage considering theMinimum Spanning Tree,shortest path distribution and network diameter.It is found that these are the very effective ways to find influential and central nodes from such big social networks like Facebook,Instagram,Twitter,LinkedIn,etc.
文摘Community detection is one of the most fundamental applications in understanding the structure of complicated networks.Furthermore,it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships.Networking structures are highly sensitive in social networks,requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks.In addition,they miss out on accurately identifying clusters.Since single-objective optimization cannot always generate accurate and comprehensive results,as multi-objective optimization can.Therefore,we utilized two objective functions that enable strong connections between communities and weak connections between them.In this study,we utilized the intra function,which has proven effective in state-of-the-art research studies.We proposed a new inter-function that has demonstrated its effectiveness by making the objective of detecting external connections between communities is to make them more distinct and sparse.Furthermore,we proposed a Multi-Objective community strength enhancement algorithm(MOCSE).The proposed algorithm is based on the framework of the Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),integrated with a new heuristic mutation strategy,community strength enhancement(CSE).The results demonstrate that the model is effective in accurately identifying community structures while also being computationally efficient.The performance measures used to evaluate the MOEA/D algorithm in our work are normalized mutual information(NMI)and modularity(Q).It was tested using five state-of-the-art algorithms on social networks,comprising real datasets(Zachary,Dolphin,Football,Krebs,SFI,Jazz,and Netscience),as well as twenty synthetic datasets.These results provide the robustness and practical value of the proposed algorithm in multi-objective community identification.
基金Supported by the National Social Science Foundation of China:the Sociological Study on the Technology Adoption Behaviors of Farmers(08BSH049)~~
文摘[Objective] To analyze the key factor in agricultural technology diffusion- technology support, and to explore the method to quicken the diffusion of agricultural technology. [Method] The technology acquisition advantage of social network was il- lustrated by summarizing the status and characteristics of agricultural technology and technology supporting types in the process of agriculture technology diffusion. [Result] The multi-layer, complex, persistence, systematization features of agricultural technol- ogy require support and help of technology from surrounding social network to ulti- mately internalize the technology. [Conclusion] Using social networks for the technol- ogy support will be a powerful supplement to the system of agricultural technology diffusion.
文摘Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We used a joint network model- ing approach to examine the interdependencies between two behavioral networks, aggression and status signaling, from four sta- ble and three unstable groups of rhesus macaques in order to identify characteristic patterns of network interdependence in stable groups that are readily distinguishable from unstable groups. Our results showed that the most prominent source of aggres- sion-status network interdependence in stable social groups came from more frequent dyads than expected with opposite direc- tion status-aggression （i.e. A threatens B and B signals acceptance of subordinate status）. In contrast, unstable groups showed a decrease in opposite direction aggression-status dyads （but remained higher than expected） as well as more frequent than ex- pected dyads with bidirectional aggression. These results demonstrate that not only was the stable joint relationship between ag- gression and status networks readily distinguishable from unstable time points, social instability manifested in at least two differ- ent ways. In sum, our joint modeling approach may prove useful in quantifying and monitoring the complex social dynamics of any wild or captive social system, as all social systems are composed of multiple interconnected networks [Current Zoology 61 （1）： 70-84, 2015].
文摘Invasive alien pest insect species represent a major threat for agriculture and biodiversity. Because chemical treatments employed to contrast such pests elicit serious environmental and human health problems, a great effort is currently directed to develop long term and environmentally friendly biological control strategies. However, the successful application of some promising techniques, such as the Sterile Insect Technique （SIT）, requires a deep knowledge of the pest basic biology. Here, we argue that understanding pest sexual biology using a social network approach can significantly improve the performance of con- trol strategies. For example, SIT may benefit from understanding how individuals interact and how males accede to reproduction, in order to target the most reproductively active and polygamic males. In this paper we studied the socio-sexual networks of the Asian red palm weevil （RPW） Rhynchophorusferrugineus, a worldwide invader which is causing heavy economic impacts on several palm species. We found that the RPW has a highly promiscuous mating system, characterized by forced interruptions of pair copulations by additional males. The social network is highly non-random nor regular： few males almost monopolize repro- duction, behaving as key-players in the network of matings. Additionally, males have a stable pattern of sexual behaviour over time. We use RPW social network as a case study to direct the development of management techniques such as SIT strategy [Current Zoology 61 （1）： 85-97, 2015].
基金sponsored by the National Natural Science Foundation of China under grant number No. 61100008 the Natural Science Foundation of Heilongjiang Province of China under Grant No. LC2016024
文摘In this paper, we discuss building an information dissemination model based on individual behavior. We analyze the individual behavior related to information dissemination and the factors that affect the sharing behavior of individuals, and we define and quantify these factors. We consider these factors as characteristic attributes and use a Bayesian classifier to classify individuals. Considering the forwarding delay characteristics of information dissemination, we present a random time generation method that simulates the delay of information dissemination. Given time and other constraints, a user might not look at all the information that his/her friends published. Therefore, this paper proposes an algorithm to predict information visibility, i.e., it estimates the probability that an individual will see the information. Based on the classification of individual behavior and combined with our random time generation and information visibility prediction method, we propose an information dissemination model based on individual behavior. The model can be used to predict the scale and speed of information propagation. We use data sets from Sina Weibo to validate and analyze the prediction methods of the individual behavior and information dissemination model based on individual behavior. A previously proposedinformation dissemination model provides the foundation for a subsequent study on the evolution of the network and social network analysis. Predicting the scale and speed of information dissemination can also be used for public opinion monitoring.
基金supported by the Research Fund for the Doctoral Program(New Teachers)Ministry of Education of China under Grant No.20121103120032+2 种基金Humanity and Social Science Youth foundation of Ministry of Education of China under Grant No.13YJCZH065General Program of Science and Technology Development Project of Beijing Municipal Education Commission of China under Grant No.km201410005012Open Research Fund of Beijing Key Laboratory of Trusted Computing,Open Research Fund of Key Laboratory of Trustworthy Distributed Computing and Service(BUPT),Ministry of Education
文摘Online social networks have gradually permeated into every aspect of people's life.As a research hotspot in social network, user influence is of theoretical and practical significant for information transmission, optimization and integration. A prominent application is a viral marketing campaign which aims to use a small number of targeted infl uence users to initiate cascades of infl uence that create a global increase in product adoption. In this paper, we analyze mainly evaluation methods of user infl uence based on IDM evaluation model, Page Rank evaluation model, use behavior model and some other popular influence evaluation models in currently social network. And then, we extract the core idea of these models to build our influence evaluation model from two aspects, relationship and activity. Finally, the proposed approach was validated on real world datasets,and the result of experiments shows that our method is both effective and stable.
