Automatic Social Circle Detection Using Multi-View Clustering

Background: Developing the knowledge base on the impact of aphasia on people's social lives has become increasingly important in recent times to further our understanding of the broad consequences of communication disability and thus provide appropriate services. Past research clearly indicates that relationships and social activities with family members and others undergo change with the onset of aphasia in an individual, however more evidence of a quantitative nature would be beneficial. Aims: The current research furthers our knowledge by quantifying chronically aphasic older people's regular social contacts and social activities, and places them in context by comparing them with healthy older people of similar age and education. Methods & Procedures: A total of 30 aphasic participants aged 57 to 88 years, and 71 non‐aphasic controls aged 62 to 98 years were interviewed by a speech and language therapist using self‐report measures of Social Network Analysis (Antonucci & Akiyama, 1987) and Social Activities Checklist (Cruice, 2001, in Worrall & Hickson, 2003). Demographic information was also collected. Descriptive statistics are presented and independent samples t tests were used to examine differences between the groups. Outcomes & Results: Participants with primarily mild to moderate aphasic impairment reported a considerable range of social contacts (5–51) and social activities (8–18). Many significant differences were evident between the two groups' social contacts and activities. On average, aphasic participants had nine fewer social contacts (mainly “friend” relationships) and three fewer social activities (mainly “leisure” activities) than their non‐aphasic peers. The majority of controls were satisfied with their social activities, whereas the majority of aphasic participants were not and wanted to be doing more. There were some general similarities between the groups, in terms of range of social contacts, overall pattern of social relationships, and core social activities. Conclusions: Older people with chronic aphasia had significantly fewer social contacts and social activities than their peers. People with aphasia expressed a desire to increase the social activity of their lives. Given the importance of leisure activity and relationships with friends as well as family for positive well‐being, speech and language therapists may direct their rehabilitation efforts towards two areas: (1) conversational partner programmes training friends to maintain these relationships; and (2) encouraging and supporting aphasic clients in leisure activities of their choice.

Rapid technological developments have affected all aspects of people's social life, including in the field of marriage. One indication is the use of teleconference developments as a medium for conducting marriage contracts, but the problem is, Islamic law has not specifically regulated the rules or laws of marriage contracts through teleconference technology or other online media, while the development of information technology is faster and faster when compared to development of legal substance. The issue of the marriage contract via teleconference caused controversy because of differences in interpretation of the concept of the unity of the assembly. This research is a type of normative legal research. Normative legal research that focuses on legal principles related to the implementation of the marriage contract. This study is descriptive in nature, collecting information about a teleconference marriage contract phenomenon. The approach used is a normative theological approach, phenomenology and philosophy. The analytical knife uses the maqashid shariah theory in observing the marriage contract by teleconference. The research findings show that the marriage contract through teleconference which was carried out during the Covid-19 pandemic was reviewed according to maqashid shariah is a legal event that is allowed, and this will be an alternative to avoid harm as a goal to maintain the human soul.

BackgroundThe dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change.ObjectiveThe intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions.MethodsEight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where “population” included child or adult populations, including healthy and disease populations; “intervention” involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; “comparator” was either a control group or within subject in the case of pre-post study designs; “outcomes” included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and “study design” included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen’s d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized.ResultsA total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included commercial online health social network websites (n=2), research health social network websites (n=3), and multi-component interventions delivered in part via pre-existing popular online social network websites (Facebook n=4 and Twitter n=1). Nine of the 10 included studies reported significant improvements in some aspect of health behavior change or outcomes related to behavior change. Effect sizes for behavior change ranged widely from −0.05 (95% CI 0.45-0.35) to 0.84 (95% CI 0.49-1.19), but in general were small in magnitude and statistically non-significant. Participant attrition ranged from 0-84%. Engagement and fidelity were relatively low, with most studies achieving 5-15% fidelity (with one exception, which achieved 105% fidelity).ConclusionsTo date there is very modest evidence that interventions incorporating online social networks may be effective; however, this field of research is in its infancy. Further research is needed to determine how to maximize retention and engagement, whether behavior change can be sustained in the longer term, and to determine how to exploit online social networks to achieve mass dissemination. Specific recommendations for future research are provided.

The development of science, technology and information (science and technology) is very fast and globalization nowadays occur positive and negative impacts on people's lives, both individual and social life. The positive impact of the development of science and technology and the globalization of the labor market is opening opportunities in accordance with the needs of society and the state. While the negative impact is the changing values and norms of life that is often in contradiction with the norms and values of life that has existed in the community. In this context, education, especially primary education, plays a very important to preserve and protect the norms and positive life values that already exist in the society of a country from the negative effects of science and technology development and globalization. The education process is right and quality provided supplies and power to maintain the "identity" of the negative effects of globalization, not only for the interests of individual learners, but also for the benefit of society and the state. National policy development of the noble character education into the national education system is a strategic effort to equip future generations with the noble character of the nation as the identity of Indonesia in global competition. With the character education that is applied systematically and sustainably, a child will be emotionally intelligent. Emotional intelligence is important provision in preparing children to meet the future, because someone will be more easily and successfully face all kinds of life challenges, including the challenge to succeed academically.

Social media use has become an integral part of children's and adolescents' lives. It has become a novel way of interaction among people and influences people's social lives and public opinion as well as people's purchasing decisions and businesses. Any website or platform that allows social interaction is considered to be a social media site. Social media use among children in 25 European countries has been reported to be 38% among 9-12year olds and 77% among those aged 13-16years. All these children report having their own profile on at least one social network site. While social networking provides children and adolescents with many opportunities and benefits, it also carries many risks. Among the benefits are socialization and communication enhancement, improving learning skills, positive impact on education and getting health information. Potential risks of social media use include falsifying age and identity, cyberbullying, sexting, Facebook depression, gamification, glamourization, cyberostracism and sleep disturbances.Conclusion: Paediatricians play a vital role in promoting the physical, mental and social welfare of all children. There is a critical need for paediatricians to play an active role, guiding children and families appropriately through the impact of social networking, in order to become a real driver of children's development.

Recent years, social network has attracted many attentions from research communities in data mining, social science and mobile etc, since users can create different types of information due to different actions and the information gives us the opportunities to better understand the insights of people's social lives. Co-clustering is an important technique to detect patterns and phenomena of two types of closely related objects. For example, in a location based social network, places can be clustered with regards to location and category, respectively and users can be clustered w.r.t. their location and interests, respectively. Therefore, there are usually some latent goals behind a co-clustering application. However, traditionally, co-clustering methods are not specifically designed to handle multiple goals. That leaves certain drawbacks, i.e., it cannot guarantee that objects satisfying each individual goal would be clustered into the same cluster. However, in many cases, clusters of objects meeting the same goal is required, e.g., a user may want to search places within one category but in different locations. In this paper, we propose a goal-oriented co-clustering model, which could generate co-clusterings with regards to different goals simultaneously. By this method, we could get co-clusterings containing objects with desired aspects of information from the original data source. Seed features sets are pre-selected to represent goals of co-clusterings. By generating expanded feature sets from seed feature sets, the proposed model concurrently co-clustering objects and assigning other features to different feature clusters.

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.

There has been a recent unprecedented increase in the use of Online Social Networks (OSNs) to expand our social life, exchange information and share common interests. Many popular OSNs today attract hundreds of millions of users who share tremendous amount of data on it such as Facebook, Twitter, and Buzz. Given the huge business opportunities OSNs may bring, more and more new social applications has emerged on the Internet. For these newcomers in the social network business, one of the first key decisions to make is to where to deploy the computational resources to best accommodate future client requests. In this work, we aim at providing useful suggests to the new born social network providers (freshman) on the intelligent server placement, by exploring available public information from existing social network communities. In this work, we first propose three scalable server placement strategies for OSNs. Our solution can scalably select server locations among all the possible locations, at the same time reducing the cost for inter-user data sharing.

Online social networks (OSNs) have gained soaring popularity and are among the most popular sites on the Web. With OSNs, users around the world establish and strengthen connections by sharing thoughts, activities, photos, locations, and other personal information. However, the immense popularity of OSNs also raises significant security and privacy concerns. Storing millions of users' private information and their social connections, OSNs are susceptible to becoming the target of various attacks. In addition, user privacy will be compromised if the private data collected by OSNs are abused, inadvertently leaked, or under the control of adversaries. as a result, the tension between the value of joining OSNs and the security and privacy risks is rising.;To make OSNs more secure and privacy-preserving, our work follow a bottom-up approach. OSNs are composed of three components, the infrastructure layer, the function layer, and the user data stored on OSNs. For each component of OSNs, in this dissertation, we analyze and address a representative security/privacy issue. Starting from the infrastructure layer of OSNs, we first consider how to improve the reliability of OSN infrastructures, and we propose Fast Mencius, a crash-fault tolerant state machine replication protocol that has low latency and high throughput in wide-area networks. For the function layer of OSNs, we investigate how to prevent the functioning of OSNs from being disturbed by adversaries, and we propose SybilDefender, a centralized sybil defense scheme that can effectively detect sybil nodes by analyzing social network topologies. Finally, we study how to protect user privacy on OSNs, and we propose two schemes. MobiShare is a privacy-preserving location-sharing scheme designed for location-based OSNs (LBSNs), which supports sharing locations between both friends and strangers. LBSNSim is a trace-driven LBSN model that can generate synthetic LBSN datasets used in place of real datasets. Combining our work contributes to improving security and privacy in OSNs.

Online social networking usage is growing rapidly, especially among at-risk populations, such as men who have sex with men (MSM). However, little research has studied the relationship between online social networking usage and sexual risk behaviors among at-risk populations. One hundred and eighteen Facebook-registered MSM (60.1% Latino, 28% African American; 11.9% other) were recruited from online (social networking websites and banner advertisements) and offline (local clinics, restaurants and organizations) venues frequented by minority MSM. Inclusion criteria required participants to be men who were 18 years of age or older, had had sex with a man in the past 12 months, were living in Los Angeles, and had a Facebook account. Participants completed an online survey on their social media usage and sexual risk behaviors. Results from a multivariable regression suggest that number of sexual partners met from online social networking technologies is associated with increased: 1) likelihood of having exchanged sex for food, drugs, or a place to stay within the past 3 months; 2) number of new partners within the past 3 months; 3) number of male sex partners within the past 3 months; and 4) frequency of engaging in oral sex within the past 3 months, controlling for age, race, education, and total number of sexual partners. Understanding the relationship between social media sex-seeking and sexual risk behaviors among at-risk populations will help inform population-focused HIV prevention and treatment interventions.

With the rapid development of We-media technology and network technology, wechat, Weibo, Facebook and other social networking sites have gradually become necessary social channels in People's Daily life and work. People can build diversified relationships through social media at any time, so as to form virtual online social networks of different levels and strength. Since online social networks are composed of dynamic users and interactive relationships, supporting the timely exchange of network information and data, research on key users of network marketing in the context of new media development can help enterprises orderly complete product promotion and research and development, which has a positive impact in the development of modern society. Therefore, on the basis of understanding the development background of new media, this study regards real online social network data as the analysis target, and discusses the application of false information control and efficient network marketing based on the analysis of key figures in persistent topics. The final results show that the proposed algorithm is effective in real data sets.

Online social media network has become part of human life by transforming the way users create new social relations or relate with family and friends. Online social network (OSN) has drastically increased the rate at which people interact with each other by simplifying the means of communication. However, privacy is raising a serious concern. All user generated data within the OSN system need to be protected against unauthorized friends or hackers or even against the provider of OSN. Many research works are going on to encounter the privacy issues in OSN. This paper analyses the limitations of the recent work being done in this field and proposes an efficient abstract solution to them.

Many business applications rely on their historical data to predict their business future.The marketing products process is one of the core processes for the business.Customer needs give a useful piece of information that helps to market the appropriate products at the appropriate time.Moreover, services are considered recently as products.The development of education and health services is depending on historical data.For the more, reducing online social media networks problems and crimes need a significant source of information.Data analysts need to use an efficient classification algorithm to predict the future of such businesses.However, dealing with a huge quantity of data requires great time to process.Data mining involves many useful techniques that are used to predict statistical data in a variety of business applications.The classification technique is one of the most widely used with a variety of algorithms.In this paper, various classification algorithms are revised in terms of accuracy in different areas of data mining applications.A comprehensive analysis is made after delegated reading of 20 papers in the literature.This paper aims to help data analysts to choose the most suitable classification algorithm for different business applications including business in general, online social media networks, agriculture, health, and education.Results show FFBPN is the most accurate algorithm in the business domain.The Random Forest algorithm is the most accurate in classifying online social networks (OSN) activities.Naïve Bayes algorithm is the most accurate to classify agriculture datasets.OneR is the most accurate algorithm to classify instances within the health domain.The C4.5 Decision Tree algorithm is the most accurate to classify students' records to predict degree completion time.

Recently, communication and sharing the information through online social network (OSN) grows very fast in day to day life. As user share important data through online social network, therefore providing security and privacy to the online social network becomes the challenging task for the researchers. Moreover, for increasing the social connections and get the information from the particular group of people user needs to search the new friends and add them in the friend list. Now a days there isa friend recommendation method which was used by many online social networks, this method recommended the friend list to the user. As the privacy of these friend recommendation methods is the most significance task for the researchers and for the online social networks. Basically an online social network focused on the millions people's profile to spend time on an online social network, also implementing an OSN clients social circles, by using recommended suggestions. In this system, the main focus is on privacy and security of the online social network. This system basically focuses to support the users of online social network by secure trust creation with a stranger. This is achieved with multi-hop recommendation process. In the proposed method, the system provides privacy to the online social network from which system is allowing users to enhance their social networks. Existing system used secure KNN algorithm for securing social network. By using KNN algorithm, distance based learning is unclear. It is sort of distance and their component to use for the best results and calculation is very expensive. To overcome this limitation and to improve the precision, the proposed frame-work makes use of secure social coordinate matching with a Naive Bayes classifier. Also the privcy of social coordinates is maintained with Pailier encryption algorithm. Experimental results demonstrate that the proposed system is secure and time efficient than the existing one. Memory consumption is also improved with the proposed system.

Despite the recent popularity of online social networks, there are few available studies that explain the differences between real life and internet social networks. Authoritative information about the outcomes of using social networking websites is even more sparse. In an attempt to close this literature gap, this exploratory study found that online social networks and real life social networks are significantly different in terms of social network size. The results also show that gender and extroversion are the major predictors of both online social network size and time spent online for social networking. Perhaps the most interesting finding is the negative impact of self-esteem on inclusion of strangers in online social networks. Additionally, directions for future research are provided.