AHSCAN: Agglomerative Hierarchical Structural Clustering Algorithm for Networks

Human mobility data such as global positioning system (GPS) data from mobile phones and smart card data of public transportation have been used for the analysis of a city. Those studies have attempted to create networks whose nodes represent areas of the city and whose edges represent human flows between areas. Network clustering methods are applied to those networks for extracting community structures of cities. Although many studies have attempted to extract community structures of cities using human mobility data and network clustering methods, little has been explored about which method is the most effective, in terms of the accuracy and the amount of information of extracted clusters. In this paper, we propose evaluation metrics for evaluating network clustering methods based on the geographical cohesiveness, the regularity, and the amount of information of extracted clusters. We use smart card data of public transportation collected in Japan for testing the effectiveness of each method. We compare two types of origin-destination matrices for constructing networks and four types of network clustering methods including two types of bipartite network clustering methods. The results confirmed that a bipartite network clustering method considering multi-facet characteristics of each cluster and the functional relations between areas of a city shows the most accurate and richest information about community structures of cities.

Contributors

We consider the clustering problem in a private social network, in which all vertices are independent and private, and each of them knows nothing about vertices other than itself and its neighbors. Many clustering methods for networks have recently been proposed. Some of these works have dealt with a mixed network of assortative and disassortative models. These methods have been based on the fact that the entire structure of the network is observable. However, entities in real social network may be private and thus cannot be observed. We propose a privacy-preserving EM algorithm for clustering on distributed networks that not only deals with the mixture of assortative and disassortative models but also protects the privacy of each vertex in the network. In our solution, each vertex is treated as an independent private party, and the problem becomes an n-party privacy-preserving clustering, where n is the number of vertices in the network. Our algorithm does not reveal any intermediate information through its execution. The total running time is only related to the number of clusters and the maximum degree of the network but this is nearly independent of the total vertex number.

In this article, we develop a clique-based method for social network clustering. We introduce a new index to evaluate the quality of clustering results, and propose an efficient algorithm based on recursive bipartition to maximize an objective function of the proposed index. The optimization problem is NP-hard, so we approximate the semi-optimal solution via an implicitly restarted Lanczos method. One of the advantages of our algorithm is that the proposed index of each community in the clustering result is guaranteed to be higher than some predetermined threshold, $p$, which is completely controlled by users. We also account for the situation that $p$ is unknown. A statistical procedure of controlling both under-clustering and over-clustering errors simultaneously is carried out to select localized threshold for each subnetwork, such that the community detection accuracy is optimized. Accordingly, we propose a localized clustering algorithm based on binary tree structure. Finally, we exploit the stochastic blockmodels to conduct simulation studies and demonstrate the accuracy and efficiency of our algorithms, both numerically and graphically.

Social networks are virtual environments created by humans through software and programs. Today, social networks have expanded and become more commonplace.Individuals identify themselves through these internet networks and use their communication methods to enable them to get in touch with people from the same or different cultures. It is known that social networks have advantages as well as some disadvantages. The main purpose of this study is to determine why, how, and how frequently students use online social communication networks, and to identify the effects of these social networks on their education and social lives according to the opinions of high school students. In this study, one of each of the three high education institutions in a city center were randomly selected and the opinions of 63 students studying at different grades of these schools were collected. According to the results of this study, a significant percentage of participants regularly benefit from social network websites. The majority of opinions indicate that the participants use social network websites with the aim of communication and education.

Abstract. Introduction. The article examines current trends in advertising campaigns on the Internet and social networks. Social networks are seen as a tool to influence the target audience and study its benefits, growth, development of companies and expanding market share. Studied the theory of the importance of social networks at the initial levels of small and medium business development, including in connection with the possibility of attracting the necessary financial resources and access to information of various kinds, and in the subsequent stages of development. An analysis of examples of companies whose growth has been largely due to the integration of development strategies through social networks. The medium- and long-term prospects for the development of the advertising industry with the mass introduction of virtual and augmented reality technologies and the expansion of 5G Internet networks were considered. Purpose. The purpose of the study is to substantiate the reasons for doing business on social networks, analysis of current trends in social networks, assessing the possibility of doing business and building marketing strategies through social networks. Results. The article describes the main trends of advertising on social networks, why is it worth to run advertising campaign on social networks, describes the social network as an advertising tool, how social networks will effectively interact with the target audience and gives examples of successful projects of large companies implemented in social networks. Were reviewed main directions of development and improvement of advertising methods in social networks, how it will happen, what is needed for this and why it is impossible to implement at this stage of development. Listed all the positive aspects that will help increase the efficiency of sales goods and services, as well as the negative aspects with the implementation of these ways. Conclusion. Development of virtual and augmented reality and also 5G techonologies: 1. Significantly increase the perception of advertising; 2. Allows you to process large amounts of information in a short time; 3. Solve the problem of oversaturation with advertising of various sources of information (billboards, newspapers, the Internet); 4. Advertising will become more relevant and timelier; 5. Advertising will become more relevant for the user, which will increase business revenue; 6. Advertising will be less intrusive, which will increase user loyalty to it. In the long run, the amount of data passively collected by technical devices around will increase, which will invariably affect the prospects for marketing development in general. With the expansion of Internet coverage around the world and the increasing availability of technical devices, the number of network users will increase, which will make it easier to interact with the intended target audience, change the ways of advertising and over time social networks will become its main location. Increasing the data collected will increase user loyalty and help make advertising less intrusive and more useful to each potential customer. Given advertising prices and audience reach, businesses will be more focused on developing brands on social media and marketing mostly online.

Community detection in social networks plays an important role in cluster analysis. Many traditional techniques for one-dimensional problems have been proven inadequate for high-dimensional or mixed type datasets due to the data sparseness and attribute redundancy. In this paper we propose a graph-based clustering method for multidimensional datasets. This novel method has two distinguished features: nonbinary hierarchical tree and the multi-membership clusters. The nonbinary hierarchical tree clearly highlights meaningful clusters, while the multimembership feature may provide more useful service strategies. Experimental results on the customer relationship management confirm the effectiveness of the new method.

Visualization and machine learning analysis of complex networks in hyperspherical space

The purpose of this study is to explore the experience of the consultant’s usage on social-network and the subsequent decisions made To this end, the following four issues will be the focus of this research: the motivation and current state of the consultant’s usage on social networking sites; the consultant’s personal decision-making considerations on social networking sites; the challenges faced by the consultant on social networking sites; the consultant’s perspective on “the usage on social networking Accordingly, the research methods used will be purposive sampling and semi-structured in-depth interviews. First, six consultants would be invited to participate in the research on the usage for social networking sites. Next, the data collected through interviews would be organized, summarized and analyzed with grounded theory. Finally, the results of the study will be discussed comprehensively. Interviewee responses to the research questions: 1.The motivation and current state of the consultant’s usage on social networking The motivation for the respondents to apply for a social networking site is to interact with friends. The current state of the respondents’ usage on social networking can be summarized as follows: respondents who have long term experience in social networking will have more than one personal site; the direction of writing and the presentation of content, will be affected by the features of social networking sites, which also affects the relationship with the audience. Furthermore, the micro-blog type community site has become an integral part of the respondents’ lives. 2.Consultant’s personal decision-making considerations on the usage on social networking There are several considerations that factor into the consultants’ decisions when using the social networking sites: openness of the community site itself, ease of to spreading on the network, convenience for browsing, privacy of their own and others, personal confidentiality and protection of personal rights and interests. Furthermore, the potential ability of social networking to influence others is an important consideration for consultants due to their roles and responsibilities. 3.The challenges faced by the consultants on social networking (A)Respondents experienced negative emotions after prying into certain cases on social networking out of curiosity. (B)Respondents with the aforementioned experience tend to readjust their perspective and actions on social networking sites. 4.The consultant’s perspective on “the usage on social networking sites (A)Consultants should not be denied the right to use social networking due to their profession. However, consultants should use such with professional integrity. (B)The ability of consultants to understand the purpose of using social networking and the information to be conveyed would enable them to have a clear concept of appropriate message content. (C)Consultants would be able to avoid posting inappropriate messages on social networking if they have a good sense of self-awareness, and are able to reflect and assess the issue on hand. (D)Consultants need to pay attention to the content of messages on community websites as they have no control over the audiences’ interpretation of it. (E)Consultants should remain professional on social networking and this includes refraining from criticisms and inferences. Discoveries derived from analysis of the interview data: 1.Psychology consultants deem that social networking have become an interactive tool that is indispensable in both life and work 2.Psychology consultants’ value of individual privacy and are conscious of their input on social networking site. 3.Psychology consultants create an identity and role for themselves through the Internet and social networking 4.Psychology consultants are affected by their professional role and ethics responsibilities when using social networking sites. 5.Psychology consultants tend to be concerned over how individuals perceive the information they posted on social networking sites. 6.Psychology consultants believe that their messages on social networking may subconsciously affect the discussion on these sites. 7.Psychology consultants are influenced by their training in ethics and this makes them extra cautious when using social networking sites. 8.Psychology consultants tend to attempt to separate the “professional” and the “personal” on social networking sites. The following conclusion can be drawn from the above research and analysis of the results: 1.Recommendations for consultants (A)The importance of the effects of personal network-related messages on the consultant’s profession, work and case relationship (B)The intention usage, and function of social networking requires care and consideration. (C)In cases of ethical dilemma, consultants should seek advice and discussion with other professionals. 2.Recommendations for consultants’ training programs (A)Inclusion of Internet knowledge in training programs so consultants are familiar with its potential. (B)There should be a focus on the ethics training of consultants. 3.Recommendations for the future research (A)Public opinion on consultants’ usage of social networking sites. Consultants’ years of service can be included as a factor in the study.

Social support networks have been become one of the mostly influential metaphors in many areas around the world, especially in terms of mitigating disaster consequences and revivifying disaster affected livelihoods. More importantly, reciprocal supports ties are more powerful in healing disaster wounds of communities. Especially social capital legacies enrich by reciprocal support networks by the ways in which making may hopes among disaster victims. In this context, the objective of this study is to investigate the social support network behaviors in supporting 16 flood-affected households in the mass flooding event occurred in 2017. Particularly, the study researched social support network behaviors at different flood inundation phases such as before, during, and after. This study collected primary data (mainly social network data) using household survey and filed observations. The study used the Social Network Analysis (SNA) method for the network data analysis. This article shows that flood affected households have received social network supports in different magnitudes at before, during, and after flood inundation phases. More importantly, provision of foods, water and basic needs, sheltering, clearing contaminated households, and emotional supports have mobilized and reciprocated among victims in reviving their livelihoods. The social support network legacies have evolved at different flood inundation phases. This study fills the gabs in the flood disaster discourse on Sri Lankan context.

Стаття присвячена дослідженню проблем використання соціальних Інтернет-мереж для запобігання злочинності, як однієї із сучасних тенденцій розвитку кримінологічної науки. Встановлено доцільність використання всього спектру можливостей соціальних Інтернет-мереж для підвищення рівня запобігання злочинності, це зокрема стосується: ведення спеціалізованих блогів; створення аудіо- та відеофайлів запобіжного характеру; моніторингу кримінологічно значимої інформації та іншого.

Source detection of rumor in social network – A review

Longitudinal social network clustering is an emerging research area with many applications. Previous research typically focuses on the development of the clusters in the longitudinal network. In this paper, we propose an alternative method for longitudinal social network clustering, in which we assume that the clustering and the evolution of the network are the results of its inner structure, the strength of the ties among the nodes in the network. We estimate the strength of the ties based on the evolution of the network over time through a continuous Markov process and then clustering the network based on the strength of the ties of the whole network. A simulation study shows that the proposed method performs well under a variety of conditions. The application of the method is illustrated through the analysis of a real set of data.

Introduction states that the creation of the Internet leads to the unification of social networks’ communication norms and rules, as wellas to the development of an artificial language of communication. They facilitate the communication of different nations’ representatives in the globalization and multiculturalism context. The aim of the article is to identify the mutual influence of communication processes in social information networks and the multiculturalism phenomenon. The socio-cultural approach methodology was used to study the social information networks communication peculiarities within the context of cultural transformations. The linguistic means of communication of cultural content were investigated through the method of cultural-semantic analysis. Research results substantiate that the language of communication in various Internet spheres social networks differ both in form and in content. However, the information and communication technologies language uses common characteristics such as emoticons, which affect emotions and feelings. Different information networks keep the same meaning for those characteristics, which makes them understandable for all users alike. The problems of social networks communication in the conditions of multiculturalism are also revealed. They relate to the existence of not one, but several variants of English language (American, Indian, Australian, etc.). Discussion deals with the research results of the philosophers and scientists who to some extent touched upon the problems of social networks communication such asS. Huntington, M. Castells, D. Ivanov, V. Lyakh, L. Orokhovskaya, V. Onoprienko, S. Yagodzinskiy. The differences between the results obtained by the author of the article and the indicated researchers are shown. Conclusion indicates that the use of computer information technologies lead to the Internet communications specific language formation. It allows the Network users to understandeach other through the words, signs, symbols in multiculturalism environment. People learn to make common ideas and interests.

BackgroundSomali immigrants and refugees to the United States are at high risk for obesity and related cardiovascular risk. Social network factors influence health behaviors and are important contributors to the obesity epidemic. The objective of this study was to describe social networks and obesity-related characteristics among adult Somali immigrants in a Minnesota city in order to inform a community-based, participatory, research-derived, social network intervention to decrease obesity rates.MethodsSurvey data (demographics, general health measures, and sociobehavioral and network measures) and height and weight measures (for calculating body mass index) were collected from adult Somali immigrants by bilingual study team members at community locations. Descriptive statistics were used to report the survey and biometric data. Logistic regression models were used to describe the basic associations of participants and network factors. Network data were analyzed to identify nodes and ties, to visualize the network, and to identify potential interventionists for a future social network intervention.ResultsOf the 646 participants, 50% were overweight or affected by obesity. The network had 1703 nodes with 3583 ties between nodes, and modularity was high (0.75). Compared with respondents of normal weight, participants who were overweight or affected by obesity had more network members who were also overweight or obese (odds ratio [OR], 2.90; 95% CI, 1.11–7.56; P = .03); this was most notable for men (OR, 4.58; 95% CI, 1.22–17.22; P = .02) and suggestive for those 50 years or older (OR, 24.23; 95% CI, 1.55–377.83; P = .03). Weight loss intention among participants who were overweight or affected by obesity was associated with number of family members and friends trying to lose weight, enabling functional network factors (social norms for weight loss, social support for healthy eating, and social cohesion), and less favorable obesogenic social norms.ConclusionsIn this community sample of Somali immigrants, distinct social networks are clustered by weight status, and social contacts and functional network characteristics are related to individuals’ weight loss intentions. These factors should be considered in weight loss interventions and programs. A social network intervention targeting weight loss, within a community-based participatory research framework, is feasible in this vulnerable population.