Social networks, which emerged due to the rapid development of modern telecommunications and information technologies that led to the emergence of the Internet, can be viewed as a phenomenon of the information society. In a short time, there has been both quantitative and qualitative growth of social networks, which have become a common phenomenon in our life and the dominant way of communicati...

This study aimed to examine the influence of utilizing social networks on the intergenerational gap between families living in District 5 of Tehran. The method to conduct the research was a kind of survey method, and a researcher-made questionnaire was applied to gather information. The sampling method is a randomized cluster, and 400 people determined the sample size by applying Cochran's form...

Social network analysis offers many measures, which are successfully utilized to describe the social network profile. One of them is node position, useful to assess the importance of a given node within both the whole network and its smaller subgroups. However, to analyze large social networks a lot of effort and resources are necessary. In this paper, some algorithms that can be utilized in th...

Social network analysis has proven to be a useful tool in analysis of many situations. We begin by giving an overview of social network analysis. We then illustrate the concepts by examining the social networks of co-authors of scholarly publications. Scholarly publication is in many ways the lifeblood of academic institutions and there are strong incentives, both in terms of prestige and finan...

In this study, we develop a theoretical model to investigate the association between social network properties, “content richness” (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we refer to its structural, position and relationship attributes....

In a social network, adoption probability refers to the probability that a social entity will adopt a product, service, or opinion in the foreseeable future. Such probabilities are central to fundamental issues in social network analysis, including the influence maximization problem. In practice, adoption probabilities have significant implications for applications ranging from social network-b...

The availability of advanced social interaction sensing technologies provides fine grained data for social network analysis. Although traditional methods of gathering social network data may be subject to human ability to recall social details, people’s rating of their closeness to persons in their network is important. This study assesses the relationship amidst closeness ratings, sensed inter...

Social networks have small-world property, hierarchical community structure, and some other properties. This paper proposes models of networks with these properties and algorithm for community structure recognition. The models are useable for testing effectiveness and efficiency of different algorithms for social network analysis. © 2010 Published by Elsevier B.V.

It is often possible to better understand group change over time through examining social network data in a spatial and temporal context. Providing that context from a text analysis perspective requires identifying locations and associating them with people. This paper presents our GeoRef algorithm to automatically do this person-to-place mapping. It involves the identification of location, and...