scholarly journals Towards Understanding the Social Characteristic of YouKu: Measurement and Analysis

2012 ◽  
Vol 6-7 ◽  
pp. 1112-1117
Author(s):  
Yong Jun Li ◽  
Chun You ◽  
Xu Dong Bao

Online Social networking services are among the most popular sites and become the fast-growing business in the Internet. In-depth understanding the social characteristic of these networks can serve to optimize current systems, to design future social network based systems, and to eventually exploit the user base for commercial purposes. In this paper, we present a large-scale measurement study and analysis on the social structure of YouKu. Our results validate the power-law, small-world and clustering coefficient properties, present the correlation and difference among four centrality properties. Finally we discuss the utilization of these structural properties for the commercial purposes.

2014 ◽  
Vol 575 ◽  
pp. 863-868
Author(s):  
Wen Li Ji ◽  
Xi Xi Cao

Recently the fast-growing business of the Internet are Online Social networking services, Online Social networking sites also become the most popular sites. In order to establish future social network which is optimized, and to eventually exploit the user base for commercial purposes, in-depth understanding the social characteristic of these networks is important. In this paper, we present a large-scale measurement study and analysis on the social structure of YouKu. Our results validate the power-law, small-world and clustering coefficient properties, present the correlation and difference among four centrality properties. Finally we discuss the utilization of these structural properties for the commercial purposes.


Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2007 ◽  
Author(s):  
Farhan Amin ◽  
Rashid Abbasi ◽  
Abdul Rehman ◽  
Gyu Sang Choi

The Internet of Things (IoT) is a recent evolutionary technology that has been the primary focus of researchers for the last two decades. In the IoT, an enormous number of objects are connected together using diverse communications protocols. As a result of this massive object connectivity, a search for the exact service from an object is difficult, and hence the issue of scalability arises. In order to resolve this issue, the idea of integrating the social networking concept into the IoT, generally referred as the Social Internet of Things (SIoT) was introduced. The SIoT is gaining popularity and attracting the attention of the research community due to its flexible and spacious nature. In the SIoT, objects have the ability to find a desired service in a distributed manner by using their neighbors. Although the SIoT technique has been proven to be efficient, heterogeneous devices are growing so exponentially that problems can exist in the search for the right object or service from a huge number of devices. In order to better analyze the performance of services in an SIoT domain, there is a need to impose a certain set of rules on these objects. Our novel contribution in this study is to address the link selection problem in the SIoT by proposing an algorithm that follows the key properties of navigability in small-world networks, such as clustering coefficients, path lengths, and giant components. Our algorithm empowers object navigability in the SIoT by restricting the number of connections for objects, eliminating old links or having fewer connections. We performed an extensive series of experiments by using real network data sets from social networking sites like Brightkite and Facebook. The expected results demonstrate that our algorithm is efficient, especially in terms of reducing path length and increasing the average clustering coefficient. Finally, it reflects overall results in terms of achieving easier network navigation. Our algorithm can easily be applied to a single node or even an entire network.


Author(s):  
Serhii Puhach

The intensive development of new information and communication technologies (ICT) has led to major changes in society. The widespread use of smartphones and mobile communications has allowed today to create new programs and services to improve human life. This development changes the established habits of human communication, the relationship between society and the environment. A social networking service (SNS) is a service (on a website or through a mobile application) that allows users to share a personal profile and establish contacts with other users. Social networking services affect the territorial organization of society and can be used for the development of both settlements and entire territories to make their development more sustainable and balanced. The study of social networking services is currently on the rise. The joint efforts of many sciences (sociology, psychology, geography, mathematics, statistics, computer science, etc.) are needed to understand the subject essence of the phenomenon and to analyze data. Approaches to the study of social networking services can be divided into three large groups: 1) in terms of human relations and relationships; 2) in terms of content distributed on the network; 3) in terms of spatial aspects of the functioning of the social network. In Ukraine, there are no detailed studies of the spatial aspects of the spread of social networking services at the local level. In the Ternopil region, there is a pattern of concentration of the majority of Facebook and Instagram users in the largest cities, namely Ternopil, Chortkiv, Berezhany, Kremenets. Buchach, Borshchiv, Zalishchyky, Terebovlya, and Shumsk districts stand out among the districts by the number of users. An important indicator that characterizes the spread of social networking services is the penetration rate of the social network, which is calculated as the ratio of the number of users in a certain territory to the population living in it. Cities of regional subordination differ in terms of the penetration rate of SNS. The highest values were observed in Chortkiv, Ternopil, Kremenets cities. The penetration rate of social networking services in the administrative districts of Ternopil region is much lower. A relatively high rate (over 30%) was recorded in Buchach, Berezhany and Shumsk districts. Extremely low penetration rate (less than 5%) is in Zbarazh, Chortkiv, Zboriv districts which are adjacent to the cities of regional subordination. The social networking service Instagram is inferior to Facebook in level of development, and its main users are mainly young people. However, in the territories where the rate of Facebook penetration is the lowest in the region (Ternopil, Zbarazh, Chortkiv, Zboriv districts), the predominance of Instagram is noted. Thus, the main patterns of spatial distribution of SNS’ Facebook and Instagram in Ternopil region are: concentration of users in the largest cities, especially in the regional center Ternopil City (half of Facebook and Instagram users in the region); the number of users is proportional to the population in the territorial unit; small number of users and low penetration rate of the SNS’ in the administrative districts adjacent to the cities of regional subordination Ternopil and Chortkiv; among administrative districts, higher indicators of social network development are typical for northern and southern districts in comparison with central ones. Key words: social networking service (SNS), penetration rate of the SNS, Facebook, Instagram, Ternopil region.


Author(s):  
Xin Yuan ◽  
Guo Liu ◽  
Kun Hui Ye

The small-world model provides a useful perspective and method to study the topological structure and intrinsic characteristics of high-speed rail networks (HRNs). In this paper, the P-space method is used to examine global and local HRNs in China, meanwhile the adjacency matrix is developed, then the social network analysis and visualization tool UCINET is used to calculate the spatial and attribute data of HRNs at national and local levels in China. The small-world characteristics of whole HRNs are discussed, three networks which have different properties are determined, and a comparative analysis of the small-world effect is detected. Then, the relationship between the construction of high-speed rail and regional development of China is analysed. The results show that: 1) China's HRNs have small average path length ( L ) and large clustering coefficient (C ), representing a typical small-world network; 2) Local HRNs have a certain correlation with economic development. The reasons for the difference of HRNs with respect to characteristics among regions are eventually discussed.


2017 ◽  
Author(s):  
Haoming Guan ◽  
Honxu Wei ◽  
Xingyuan He ◽  
Zhibin Ren ◽  
Xin Chen ◽  
...  

Urban forests can attract visitors by the function of well-being improvement, which can be evaluated by analyzing the big-data from the social networking services (SNS). In this study, 935 facial images of visitors to nine urban forest parks were screened and downloaded from check-in records in the SNS platform of Sina Micro-Blog at cities of Changchun, Harbin, and Shenyang in Northeast China. Images were recognized for facial expressions by FaceReaderTM to read out eight emotional expressions: neutral, happy, sad, angry, surprised, scared, disgusted, and contempt. The number of images by women was larger than that by men. Compared to images from Changchun, those from Shenyang harbored higher neutral degree, which showed a positive relationship with the distance of forest park from downtown. In Changchun, the angry, surprised, and disgusted degrees decreased with the increase of distance of forest park from downtown, while the happy and disgusted degrees showed the same trend in Shenyang. In forest parks at city center and remote-rural areas, the neutral degree was positively correlated with the angry, surprised and contempt degrees but negatively correlated with the happy and disgusted degrees. In the sub-urban area the correlation of neutral with both surprised and disgusted degrees disappeared. Our study can be referred to by urban planning to evaluate the perceived well-being in urban forests through analyzing facial expressions of images from SNS.


2013 ◽  
pp. 1294-1314
Author(s):  
Keith A. Bauer

The social consequences of the internet are profound. Evidence of this can easily be found in the enormous body of literature discussing its impact on democracy, globalization, social networking, and education. The implications of the internet for medicine have likewise received a great deal of attention from policy makers, clinicians and technology theorists. Medical privacy, in particular, has garnered the lion’s share of attention. Nevertheless, research in this area has been lacking because it either fails to unpack the conceptual and ethical complexities of privacy or overestimates the power of technology and policy to protect our medical privacy. The aims of this chapter are twofold. The first is to provide a nuanced explication of the concept of privacy, and, second, to argue that e-medicine and the policies supposedly designed to protect the privacy and confidentiality of personal health information fail to do so and in some instances make their violations easier to commit.


Author(s):  
Keith A. Bauer

The social consequences of the internet are profound. Evidence of this can easily be found in the enormous body of literature discussing its impact on democracy, globalization, social networking, and education. The implications of the internet for medicine have likewise received a great deal of attention from policy makers, clinicians and technology theorists. Medical privacy, in particular, has garnered the lion’s share of attention. Nevertheless, research in this area has been lacking because it either fails to unpack the conceptual and ethical complexities of privacy or overestimates the power of technology and policy to protect our medical privacy. The aims of this chapter are twofold. The first is to provide a nuanced explication of the concept of privacy, and, second, to argue that e-medicine and the policies supposedly designed to protect the privacy and confidentiality of personal health information fail to do so and in some instances make their violations easier to commit.


2019 ◽  
Vol 9 (S1) ◽  
pp. 64-67
Author(s):  
R. Sebastiyan ◽  
V. Rameshbabu

Since the tremendous growth of the internet, the social networking media have become an essential part in the everyday life of academic people. This study tries to find and fill the gap between the teaching and learning in the academic culture of engineering institution by selecting the best social network media to promote and develop online quality content of educational resources. This kind of study pulse the mentality of academic student in private engineering institution through structural questionnaire survey method have been taken and made the best situation solution. The study recommends that academic students should record scholarly accomplishment of gigantic against successive accessing social network media.


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