International Journal of Computer Application Issue 4, Volume 3 (May-June 2014) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797

Review of Social Networks and On-Line Web Communities

1Sanjeev Dhawan, 2Kulvinder Singh, 3Vandana Khanchi 1,2Faculty of Computer Science & Engineering, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra-136119, Haryana, India. 3M.Tech. (Software Engineering) Research Scholar, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra-136119, Haryana, India.

Abstract: Due to multifaceted dimensions of client server based Web technologies, new medium of linking people has emerged via social networks for collaboration in several on-line communities. Social networking sites are basically a shift between the public and private information. Nowadays 1.5 billion people across the world have their profiles in online social networking sites. WWW has become the single largest source of information since online social networking sites. The structure of this paper is framed into five sections. Section-I presents the background and introduction related to the and on-line Web communities, section- II describes the use of general concepts, network models and network graph for analyzing the taxonomy and techniques used in social networks, section-III reviews the related literature work about online social network and on-line Web communities, section-IV investigates the positive and negative aspects of online social network , and finally section-V provides the conclusion of the social networks. In this paper an attempt has been made to review and discover the techniques to investigate the users’ behavior on the social networks.

Keywords: On-line social networks, models, network analysis, social network graphs, WWW.

1. Introduction

Online social networks analysis is a potential research direction to investigate the structures and associations of social networks, like analyses of centrality, density, centrality etc. in social network framework [1]. In current years, on-line social networking sites has become a very popular and interesting application in the age of Web 2.0 [2], that enables users to share, communicate, interact on the World Wide Web [3]. Social networks, such as and are vital online communities that enable users to come together, interact and share things such as audios, photographs or other files. Social networks enable the users to make short messages, commonly in the form of a mobile phone text message but exchanged among a group. People use the social sites to ask their relations questions, say how they think today and what they are up to, to make comment on something they can seen on someone’s page. These sites are today in exploiting what are known as Web 2.0 technologies. Currently, the Websites that are made based on the Web 2.0 concepts have becoming the key stream in WWW typically for those social networking sites, such as Blog, Web album, friends making Website, etc. A social network is the network of communications and relationships among social entities such as individuals, class of individuals, and organizations [4].

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International Journal of Computer Application Issue 4, Volume 3 (May-June 2014) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797

2. General Concepts in Social Network Analysis

(i) Ties: Ties or links connect two and more graph nodes. Several human behaviors, such as information- sharing, advice seeking, lending money to somebody are directed links and for examples co- memberships undirected ties.

(ii) Betweenness: The degree to which a node lies between other network nodes. This evaluates the connectivity of the node's neighbors, the nodes which bridge clusters have higher value.

(iii) Centrality: The calculation of centrality detect the most popular actors, typically the star or the “main” players, that is, those that are mainly involved in associations with other network members. The most crucial centrality measures are: Betweenness centrality, Degree centrality, and Closeness centrality.

(iv) Closeness: The extent an individual node is near all other individuals’ nodes in a network (directly or indirectly).

(v) Clique: A clique is a sub-graph in a graph in which any node is directly linked to any other node of the sub-graph.

(vi) Clustering coefficient: A calculation of the likelihood that two links of a node are associates them. A greater clustering coefficient shows a greater 'cliquishness'.

(vii) Cohesion: The extent to which users are associated directly to each other through cohesive bonds. Groups are detected as cliques if every user is directly connected to every other individual, social circle if there is less stringency of direct contact, that is imprecise, or as structurally cohesive blocks if precision is needed.

(viii) Density: Density is an estimation of the closeness of a network. Given a number of nodes, the more ties between them, the greater the density. Its formal definition is as given below. If the number of nodes in a social network is n, and the number of links l, then the density is,

ρ = 2l/n*(n-1) for directed graph (1)

ρ = l/n*(n-1) for undirected graph (2)

(ix) length: Nodes may be directly linked by a line, or they may be indirectly linked by a sequence of lines. A sequence of lines in a graph is called a “walk”, and a walk in that each point and each line are separate is called a path. The length of a path is calculated by the number of lines that makes it up.

(x) Reach: The extent to which any member of a network can reach other members of the network.

2.1 Social Network Models

A. Using formal methods to represent Social Networks: One reason for using graphical and mathematical techniques in social network is to express the descriptions of networks systematically and compactly. Other reason for using (particularly mathematical) formal methods for constructing social networks is that mathematical representations enable us to apply computers to the study of network data.

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International Journal of Computer Application Issue 4, Volume 3 (May-June 2014) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797

B. Using Graphs to show Social Relations: Network analysis uses (mainly) one type of graphic display that made of points to show actors and edges to represent relations. When sociologists used this medium of graphing things from the mathematicians, they renamed their social graphs as “sociograms”.

C. Using Matrices to Relations: The most general form of matrix in social network is a very simple one made of as several rows and columns as there are users in our data set, and where the elements show the links between the actors.

2.2 Social Network Graphs

The social graph is a widely-used and effective mathematical tool to show the relationships among users in OSNs, that benefits the analysis of social communications and user behavior characterization. Generally social networks can be represented as directed graphs (e.g., latent graph, following graph) or undirected graphs (e.g., friendship graph, interaction graph) with respect the properties of OSNs.

Table 1: List of four different kinds of social graphs.

Type Edge

Interaction graph Visible interaction, for example posting on Friendship graph Friendshipwa between people

Latent graph Latent interaction, like browsing profile Following graph Subscribe to receive all massage wa wa wall 3. Related Work

Since the development of and the World Wide Web has permitted us to analysis large-scale social networks, there has been increasing interest in social network analysis [5]. Selecting populations for research is problematic and implementing online social network tools may facilitate the recruitment process. This research examined recruitment through ’s @reply mechanism and compared the results to other survey recruitment process. Four methods were utilized to recruit survey providers to a survey about social networking sites; Facebook recruitment, Twitter recruitment process for a pre-test, self-selected survey takers, and a retweet by a potential Twitter user. The research presented the techniques used to create recruitment using Twitter successful. These results indicated that recruitment through online social network sites for example Twitter is a useful recruitment method and may be helpful to understand growing internet based phenomena [6]. By investigating user-given messages assisted local communities in getting up-to-date information; emergency rescuers in giving assistance with respect to the requirement of the populace in a timely manner or government agencies in reviewing and developing approaches to use similar information to better coordinate, centralize, manage and plan disaster relief both during and after the event [7]. Golubi et al. [8] presented that the use of among higher education institutions in Croatia is not so spread. An unknown on-line survey about the necessity of institutional existence on social networks was performed during a ten-day period in May 2011 and involved a questionnaire that was distributed to employees and students of two Zagreb based education institutions (the Faculty of Humanities and Social Sciences and employees of the University Computing Centre).

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International Journal of Computer Application Issue 4, Volume 3 (May-June 2014) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797

The goal of the on-line survey was to gather feedbacks and opinions on the need for official existence of higher institutions on a Web based social networks [9]. Facebook is the most popular social network having the highest number of users. LinkedIn network, in the age class between 34 to 45 years containing the highest number of users. Interestingly LinkedIn, for gender base investigation, for the age groups of 34-45, numbered less than male users. This indicated that male professional out number instead female users for the same age groups (34- 45). In a similar area, J.L. Sanchez et al. [10] demonstrated different utilization of social media in education and working school of computer science at the University of La Laguna. Today not all the Universities understand the value of the social media for working insertion and teaching .Although both the students and teachers make use of the online social networks. In USA, 100 percent of the universities utilized social media in some way. Broadly used social sites among American students Facebook (98%), Twitter (84%), Linkedln (47%). Laine et al. [11] suggested that while some social networking sites for example or are fully social, others such as Flickr, YouTube and LiveJournal are highly content oriented although maintaining a social component. This is amongst the task concerning with YouTube groups in general, not only in the form of categories, and they were amongst the first to study what excite group membership in YouTube in the way of other observable group activities. Durr et al. [12] stated that at present, the rapid evolution of Online Social Networks (OSN) has great influence on our global community’s communication structure. A fundamental problem during accessing the utilization of OSNs is given by non-enough guarantee of its users’ informational self-determination and the spreading of non social content. In this paper they provided thorough mechanism to search the requirements with guarantee compliance with its users’ security and privacy demands. Furthermore, they presented a new non-centralized multi-domain OSN design that integrated with requirements. Their concept represented the basis for a secure and privacy-improved OSN architecture that remove the problem of socially non-tolerable content dissemination. Potdar et al. [13] presented that social Networking is broadly used and accepted in and outside every organization. Yet it was observed that there are several users face different security implications while accessing these online social networking Websites. These security difficulties are identity stealing of personal, theft, and professional data and so on. Researchers had discussed various types of security measures and security issues practiced by citizens of Pune city in India during working on social networking Websites. This paper was presented on the major issues of security and it also concerned with possible solutions on these security issues [13]. Smartphone (like Android and iPhone based Smartphone) sales are created to surpass desktop PCs. In Smartphone sales Android beats iPhone, they are commonly designed as open, networked and networked to give different internet services and telephony. Since social media applications advent large scale of traffic over cellular networks. The growth has occurred both in form of diversity and volume in terms of traffic characteristics. Background traffic particularly made of traffic from unattended phone with applications passive phase [14]. In this study [15] they identified the rapid growth of social networks, the necessity of social networks and danger included in social networks. They then modeled the social network by cooperative game and non-zero sum game models. They explained the competition among the players in a bargaining position using cooperative game models. They then explained the role of non-zero sum game model and designed the social networks as a nonzero sum game.

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International Journal of Computer Application Issue 4, Volume 3 (May-June 2014) Available online on http://www.rspublication.com/ijca/ijca_index.htm ISSN: 2250-1797

4. Positive and Negative Aspects of Social Networks

Social networks always consist of some positive aspects and some negative aspects. Some of the positive aspects of social network are as follows:

• Easily accessible and globally available, faster communication over longer distances usually cost efficient/free, big audience blogging (Blogger, Livejournal, Youtube, Wordpress), equating computer to sociability; second life (Facebook, MySpace), easy, user friendly platform and personalization.

Moreover, the negative aspects of social network are as follows:

• Promoting fake identities (Celebrities/Political), site security (Lack of customer service, Accessibility and reliability), child safety, stalking (Party gatecrashing, crashing uninvited parties which were advertised through sites like Myspace and Facebook where anyone could see the invitation), social exploitation and censorship, lack of privacy/ control over what is public and not, encourages procrastination, tendency to compartmentalize and make false and occasionally unfair assumptions about others. Generally speaking, social networkings Websites are seen as positive among the community.

5. Conclusions

A social network is a social structure among actors, mostly individuals or organizations. It provides the channel in which they are linked by several social familiarities ranging from casual acquaintance to close familiar bonds. Social network analysis is the measuring and mapping of associations and flows between groups, people, organizations, computers or other information processing entities. The nodes in the network are the actors and groups and links represent flows or relationships between the nodes. Social networking sites have caused much debate among users across the globe. They assist us to link more easily to others, show our interests in a public forum, and allow us to forge connections instead of vast space among users.

References

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