Design and implementation of user information sharing system using location-based services for social network services

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.

Using IQA to Extract Mental Models Concerning Quality Evaluation Factors for Social Networking Services on Smartphones

Although today’s users of mobile phones are afforded increasing control as the popularity and richness of information provided by smartphones increases, how these users make choices and evaluations cannot be explicitly expressed. This study uses an acute observation of designers of technology and aesthetics to conduct a mental-model analysis of smartphones with the purpose of explicitly identifying the differences in the schemas of users. This study also modifies the mental model to evaluate the practicability of the mental model. Hence, this study investigates groups of subjects, comparing freshmen and graduating students froma college of design, and adopts a schematized data collection and analysis approach, Interactive Qualitative Analysis (IQA), to ascertain the relationships between factors and establish a complete user mental model. The study results present 11 primary affinity factors: “Pricing,” “Advertisement,” “User Interface,” “Innovation Functions,” “System Maintenance,” “Privacy,” “Utility Functions,” “Personalization,” “Network Performance,” “Customer Service,” and “Multimedia Contents.” The primary driver in evaluating smartphones is found to be “Pricing” for graduating students and “Privacy” for freshmen. The two groups share the same final effect factor, “Multimedia Contents.” This study has successfully identified differences between the different mental models of the two groups, supporting the method that using IQA to perform a quality evaluation of social networking for smartphones is effective. Consequently, platform developers can understand user demand through a mental model and can design good platform functions to effectively improve users’ experience of smartphones.

Recommending Friends Instantly in Location-based Mobile Social Networks

Differently from the general online social network(OSN),locationbased mobile social network(LMSN),which seamlessly integrates mobile computing and social computing technologies,has unique characteristics of temporal,spatial and social correlation.Recommending friends instantly based on current location of users in the real world has become increasingly popular in LMSN.However,the existing friend recommendation methods based on topological structures of a social network or non-topological information such as similar user profiles cannot well address the instant making friends in the real world.In this article,we analyze users' check-in behavior in a real LMSN site named Gowalla.According to this analysis,we present an approach of recommending friends instantly for LMSN users by considering the real-time physical location proximity,offline behavior similarity and friendship network information in the virtual community simultaneously.This approach effectively bridges the gap between the offline behavior of users in the real world and online friendship network information in the virtual community.Finally,we use the real user check-in dataset of Gowalla to verify the effectiveness of our approach.

Enhanced Cloud Service Provisioning for Social Networks

In the era of cloud computing and social networks prosperity, new requirements rise up for cloud services that meet social network’s needs. Several cloud service providers deliver social network services for cloud services users. The aim of this paper is to develop a framework to pick the best cloud service providers from group of available providers based on many Quality-of-Service (“QoS”) criteria attributes in order to enhance efficiency, accuracy and service provisioning. This paper also aims to provide a classification for QoS criteria attributes, which is divided into five main attributes and sub-attributes, helping in enhancing ranking process in the provided framework.

SNS model for providing social network channels through queries

Users can obtain the information through a basic web searching and find the answer to the questions directly,but maybe the expected answer does not exist.Besides,we do not know the update of new information in time.The online social networking services spread quickly and store many user data,but these data are worth less and may be unreliable answer to users’ questions.Users can obtain the simple answer but can not expect more additional information in knowledge question-answering(QA)system.In this paper,we design the system with the advantages of knowledge QA system,web searching and characteristics of social networking service for providing social network channel based on the query and answer without users’ contact network.The user can obtain real-time answers by the user network interested in users’ querires through the network channel of this system,get the additional information effectively and share it with others in the social network channel in this system.

Social Networks and Their Role in Current Medicine: An Indispensable Tool for Doctors

Social networks have had a substantial impact on the current methods of professional development and practice within the health services industry. They have proven to have a wide range of suitable applications that facilitate communication, training, and medical practice. Currently, there are many web systems that allow people to have a public or semi-public profile, allowing the creation of shared connections with a list of users within the same system, which may vary in nature and terminology depending on the site in which it is used, shaping the concept of the social network. The purpose of this review is to highlight the usefulness of social media networks in academic medicine and its impact on health services.

An Approach for Telecom Operators to Achieve Converged Telecom and Internet Services

This article discusses a possible approach for telecom operators to achieve converged telecom and Internet services. It involves integrally developing telecom networks and Internet businesses through the convergence of their instant news and social networking services. Some background, benefits for telecom operators, and possible challenges are analyzed. A new service convergence approach such as this can also facilitate triple-screen and multi-screen convergence in the future.

Social Networks Design of Hospital Facilitators （HFs）＂ An Empirical Study of the Case of Italy

In this paper, the author provides a representation of Italian public hospital facilitators （HFs） （clinics, regional or local community hospitals, and medical centers） by means of different types of networks. Moving from the balance scorecards of HFs, the author has analyzed the representation of those data through the use of the minimum spanning tree （MST） and the planar maximally-filtered graph （PMFG）. This paper firstly examined the amount of information provided by the two networks and then run a sensitivity analysis of the networks by varying the elements of the balance scorecards to be considered. In this way, the author obtained a quite unusual representation of the overall economic situation of Italian HFs. Moreover, the author observed the emergence of patterns which in the author＇s opinion might help policy makers to realize a more efficient allocation of financial resources among the existing HFs.

A Study on the Path of Promoting the Socialization Level of the Old--age Service in Internet

The rapid development of Intemet＋ has accelerated the integration with the traditional industry, the field of pension services is no exception, the State Department issued in 2015, ＂on the positive promotion of the Internet ＋＂ action guidance ＂clearly put forward＂ to promote the wisdom of health care industry development ＂The goal of the task, and now, the Intemet＋ has been inserted for the old age of a pair of wings, the application of technology to promote the development of pension industry. This paper analyzes the status quo of socialization of old - age service, the use ofInternet ＋ technology, to achieve the traditional pension services and the latest network technology in depth integration, scientific analysis to explore the relevant path. Intemet ＋ era of the path to choose from the following aspects Finally, Top-level design should strengthen the formulation of government policy system, promote departmental collaboration, strengthen the development of information technology standards. In addition to establish a sound network information pension service system

城乡老年人网络信息甄别能力及其影响因素——基于CLASS 2020调查数据的实证分析

提升老年人网络信息甄别能力已成为弥合数字鸿沟的重要举措。基于2020年中国老年社会追踪调查数据发现:老年人网络信息甄别能力整体水平不高,农村老年人网络信息甄别能力低于城镇老年人;年龄、文化水平、上网频率、生理健康、家庭收入水平、家庭上网指导、网络文化反哺,以及社会保障待遇、社区上网培训和上网咨询显著正向影响老年人网络信息甄别能力,其中家庭禀赋是影响老年人网络信息甄别能力最为关键的因素,社会资源次之。因此,提升老年人网络信息甄别能力需多元主体共同协作,发挥家庭成员“数字反哺”功能,加大社区老年网络信息甄别培训,并在社会层面促进城乡老年数字教育均衡发展。

Co-occurrence prediction in a large location-based social network

Location-based social network （LBSN） is at the forefront of emerging trends in social network services （SNS） since the users in LBSN are allowed to ＂check-in＂ the places （locations） when they visit them. The accurate geographi- cal and temporal information of these check-in actions are provided by the end-user GPS-enabled mobile devices, and recorded by the LBSN system. In this paper, we analyze and mine a big LBSN data, Gowalla, collected by us. First, we investigate the relationship between the spatio-temporal co- occurrences and social ties, and the results show that the co- occurrences are strongly correlative with the social ties. Sec- ond, we present a study of predicting two users whether or not they will meet （co-occur） at a place in a given future time, by exploring their check-in habits. In particular, we first intro- duce two new concepts, bag-of-location and bag-of-time-lag, to characterize user＇s check-in habits. Based on such bag rep- resentations, we define a similarity metric called habits sim- ilarity to measure the similarity between two users＇ check-in habits. Then we propose a machine !earning formula for pre- dicting co-occurrence based on the social ties and habits sim- ilarities. Finally, we conduct extensive experiments on our dataset, and the results demonstrate the effectiveness of the proposed method.

Providing Location-Aware Location Privacy Protection for Mobile Location-Based Services

Location privacy has been a serious concern for mobile users who use location-based services provided by third-party providers via mobile networks. Recently, there have been tremendous efforts on developing new anonymity or obfuscation techniques to protect location privacy of mobile users. Though effective in certain scenarios, these existing techniques usually assume that a user has a constant privacy requirement along spatial and/or temporal dimensions, which may be not true in real-life scenarios. In this paper, we introduce a new location privacy problem： Location-aware Location Privacy Protection （L2P2） problem, where users can define dynamic and diverse privacy requirements for different locations. The goal of the L2P2 problem is to find the smallest cloaking area for each location request so that diverse privacy requirements over spatial and/or temporal dimensions are satisfied for each user. In this paper, we formalize two versions of the L2P2 problem, and propose several efficient heuristics to provide such location-aware location privacy protection for mobile users. Through extensive simulations over large synthetic and real-life datasets, we confirm the effectiveness and efficiency of the proposed L2P2 algorithms.

Exploiting Geo-Social Correlations to Improve Pairwise Ranking for Point-of-Interest Recommendation

Recently, as location-based social network(LBSN) rapidly grow, point-of-interest(POI) recommendation has become an important way to help people locate interesting places. Nowadays, there have been deep studies conducted on the geographical and social influence in the point-of-interest recommendation model based on the rating prediction. The fact is, however, relying solely on the rating fails to reflect the user's preferences very accurately, because the users are most concerned with the list of ranked point-of-interests(POIs) on the actual output of recommender systems. In this paper, we propose a co-pairwise ranking model called Geo-Social Bayesian Personalized Ranking model(GSBPR), which is based on the pairwise ranking with the exploiting geo-social correlations by incorporating the method of ranking learning into the process of POI recommendation. In this model, we develop a novel BPR pairwise ranking assumption by injecting users' geo-social preference. Based on this assumption, the POI recommendation model is reformulated by a three-level joint pairwise ranking model. And the experimental results based on real datasets show that the proposed method in this paper enjoys better recommendation performance compared to other state-of-the-art POI recommendation models.

Time and Location Aware Points of Interest Recommendation inLocation-Based Social Networks

The wide spread of location-based social networks brings about a huge volume of user check-in data, whichfacilitates the recommendation of points of interest （POIs）. Recent advances on distributed representation shed light onlearning low dimensional dense vectors to alleviate the data sparsity problem. Current studies on representation learningfor POI recommendation embed both users and POIs in a common latent space, and users＇ preference is inferred basedon the distance/similarity between a user and a POI. Such an approach is not in accordance with the semantics of usersand POIs as they are inherently different objects. In this paper, we present a novel translation-based, time and locationaware （TransTL） representation, which models the spatial and temporal information as a relationship connecting users andPOIs. Our model generalizes the recent advances in knowledge graph embedding. The basic idea is that the embedding ofa 〈time, location〉 pair corresponds to a translation from embeddings of users to POIs. Since the POI embedding shouldbe close to the user embedding plus the relationship vector, the recommendation can be performed by selecting the top-kPOIs similar to the translated POI, which are all of the same type of objects. We conduct extensive experiments on tworeal-world data.sets. The results demonstrate that our TransTL model achieves the state-of-the-art performance. It is alsomuch more robust to data sparsity than the baselines.

The social determinants of health influencing obesity for the aged in the Pakpoon community context:A qualitative study

Objective:This study aimed to describe the social determinants of health influencing obesity for the aged in a community context and based on the perspectives of various stakeholders.Methods:This was qualitative content analysis study using data from the focus group,individual in-depth interview,and observation.The study population was domiciled in Pakpoon Village,Mung Dis-trict,Nakhon Si Thammarat Province,a tight-knit settlement typical of most retirement communities.Data were collected through two focus group discussions,direct observation,and in-depth interviews with 19 participants.Respondents represented key community groups:local nurses and public health officers,elderly residents,family caregivers(family members),and village health volunteers.Results:The participants shared similar perspectives about the social determinants of health influencing obesity in the aged,which spanned three themes.These were:1)neighborhood food environment(easy access to unhealthy food,no choice to recruit healthy food);2)social networks influencing obesity(family affects food choices and prohibitions on exercise;belief,and socially imposed body image per-ceptions contributing to obesity in the aged);and 3)knowledge,attitudes,and beliefs behind lifestyle choices that cause obesity in the elderly(lack of awareness,personal attitudes,job and familial duties as barriers to engaging in physical activities;over-consumption behaviors lead to obesity in older people).Conclusion:These three themes were the root causes of obesity in the elderly in Pakpoon’s retirement community.This finding suggests that policymakers and nurses can create healthy environments,both to treat and prevent obesity,by raising awareness in younger generations,providing aging the provision of healthy food choices for older adults,encouraging health care professionals to share knowledge,and by modifying the attitudes and beliefs of both caregivers and older adults.

A Privacy-Preserving Scheme for Location-Based Services in the Internet of Vehicles

Ubiquitous information exchange is achieved among connected vehicles through the increasingly smart environment.The concept of conventional vehicular ad hoc network is gradually transformed into the Internet of vehicles(IoV).Meanwhile,more and more locationbased services(LBSs)are created to provide convenience for drivers.However,the frequently updated location information sent to the LBS server also puts user location privacy at risk.Thus,preserve user location privacy while allowing vehicles to have high-quality LBSs is a critical issue.Many solutions have been proposed in the literature to preserve location privacy.However,most of them cannot provide real-time LBS with accurate location updates.In this paper,we propose a novel location privacy-preserving scheme,which allows vehicles to send accurate real-time location information to the LBS server while preventing being tracked by attackers.In the proposed scheme,a vehicle utilizes the location information of selected shadow vehicles,whose route diverge from the requester,to generate multiple virtual trajectories to the LBS server so as to mislead attackers.Simulation results show that our proposed scheme achieves a high privacy-preserving level and outperforms other state-of-the-art schemes in terms of location entropy and tracking success ratio.

Roles of mutual help of local community networks in community health activities: Improvement for the quality of life of older people in Thailand

Objectives: This study aimed to describe work and activities of community networks focusing on the improvement of the quality of life (QOL) of older people in Thailand.The understanding of the work can help enhancing the community development and strengthening of local communities and their networks.Methods: Qualitative methods including in-depth interview,observation,and focus group discussion were employed to the study.64 participants participated to the study and were recruited from 4 key actors within the community.Content analysis was used to analyze the obtained data.This study was conducted in 6 local administrative organizations (LAOs) which selected from the outstanding areas of the project.Each LAO represents one sub-district of the regions of Thailand namely;(1) the upper north,(2) the lower north,(3)the upper eastern,(4) the lower eastern,(5) the central and (6) the south.Results: The findings of this study were categorized into three main themes: (1) Social capital including people in the community,social groups,and organizations,(2) Mutual help/collaboration activities composed of six sets of activities related to social capitals working on the improvement of QOL of older people,and (3) Impacts of the mutual help/collaboration activities on older people and local communities who help to improve of QOL of older people.Conclusion: The findings are important features for the community development.These themes should be recommended for community nurses,health related groups and organizations for the improvement of QOL of older people in the community.

Modeling and Predicting of News Popularity in Social Media Sources

The popularity of news,which conveys newsworthy events which occur during day to people,is substantially important for the spectator or audience.People interact with news website and share news links or their opinions.This study uses supervised learning based machine learning techniques in order to predict news popularity in social media sources.These techniques consist of basically two phrases:a)the training data is sent as input to the classifier algorithm,b)the performance of prelearned algorithm is tested on the testing data.And so,a knowledge discovery from the data is performed.In this context,firstly,twelve datasets from a set of data are obtained within the frame of four categories:Economic,Microsoft,Obama and Palestine.Second,news popularity prediction in social network services is carried out by utilizing Gradient Boosted Trees,Multi-Layer Perceptron and Random Forest learning algorithms.The prediction performances of all algorithms are examined by considering Mean Absolute Error,Root Mean Squared Error and the R-squared evaluation metrics.The results show that most of the models designed by using these algorithms are proved to be applicable for this subject.Consequently,a comprehensive study for the news prediction is presented,using different techniques,drawing conclusions about the performances of algorithms in this study.

Locating Mobile Users Using Base Stations of Cellular Networks

The location of mobile users served by cellular networks is considered. The chosen approach assumes that location is estimated through angular triangulation with three base stations (BSs). New estimates are proposed, which are described by closed-form expressions, and are alternatives to the maximum likelihood estimate. It is shown that the accuracy of the estimate coinciding with incircle center of the bearing triangle is close to the accuracy of the maximum likelihood estimate.

The Impact of Urban Renewal on Public Service Facilities in Shenzhen during Inventory Development Stage:An Empirical Analysis of Futian District

As the material carrier of social service industry,public service facilities are important indicators to measure human settlement.With the continuous deepening of inventory development practice,urban renewal has gradually become one of the sources of supply of public service facilities.Focusing on the urban renewal activities of Futian District,Shenzhen from 2010 to 2016,the study conducts an empirical study on the pattern of public service facility networks before and after urban renewal through social network analysis.The fi ndings show that:①on the whole,the public service system in Futian District has been effectively improved during urban renewal development;②the impact of urban renewal on public service system is characterized by differentiation,among which industrial and commercial facilities have been signifi cantly improved,while educational and medical facilities have been hardly improved;③urban renewal has a clear policy orientation as an institutional means,and promoting economic restructuring and industrial reorganization is still the primary purpose of urban renewal during inventory development stage.