Social Network Analysis is attracting growing attention as social networking sites and their enabled applications transform and impact society. This paper aims to provide a comprehensive review of social network analysis state of the art research and practice. In the paper the authors’ first examine social networking and the core concepts and ingredients of social network analysis. Secondly, they review the trend of social networking and related research. The authors’ then consider modelling motivations, discussing models in line with tie formation approaches, where connections between nodes are taken into account. The authors’ outline data collection approaches along with the common structural properties observed in related literature. They then discuss future directions and the emerging approaches in social network analysis research, notably semantic social networks and social interaction analysis.
BackgroundAnalyzing content generated by users of social network sites has been shown to be beneficial across a number of disciplines. Such analysis has revealed the precise behavior of users that details their distinct patterns of engagement. An issue is evident whereby without direct engagement with end users, the reasoning for anomalies can only be the subject of conjecture. Furthermore, the impact of engaging in social network sites on quality of life is an area which has received little attention. Of particular interest is the impact of online social networking on older users, which is a demographic that is specifically vulnerable to social isolation. A review of the literature reveals a lack of knowledge concerning the impact of these technologies on such users and even less is known regarding how this impact varies across different demographics.ObjectiveThe objective of our study was to analyze user interactions and to survey the attitudes of social network users directly, capturing data in four key areas: (1) functional usage, (2) behavioral patterns, (3) technology, and (4) quality of life.MethodsAn online survey was constructed, comprising 32 questions. Each question directly related to a research question. Respondents were recruited through a variety of methods including email campaigns, Facebook advertisements, and promotion from related organizations.ResultsIn total, data was collected from 919 users containing 446 younger and 473 older users. In comparison to younger users, a greater proportion of older users (289/473, 61.1% older vs 218/446, 48.9% younger) (P<.001) stated that Facebook had either a positive or huge impact on their quality of life. Furthermore, a greater percentage of older users strongly agreed that Facebook strengthened their relationship with other people (64/473, 13.5% older vs 40/446, 9.0%younger) (P=.02). In comparison to younger users, a greater proportion of older users had more positive emotions—classified as slightly better or very good—during their engagement with Facebook (186/473, 39.3% older vs 120/446, 26.9% younger) (P<.001).ConclusionsThe results reveal that despite engaging at considerably lower rates with significantly fewer connections, older users gain a greater quality-of-life benefit. Results disclose how both cohorts vary in their use, interactions, and rationale for engaging with Facebook.
Abstract:The popularity of social networking has risen considerably in recent years, increasing opportunities for social interaction. As an approach, it has the potential to reduce the burden of social isolation for older users. However, the current state of older user engagement requires investigation. In a study, exploring the possibilities of interaction analysis to undercover user behaviours/characteristics, five aspects of younger and older online engagement were investigated comprising; connectivity, length of engagement, application usage, engagement frequency classification and profile maintenance frequency. Results derived from user generated content, enabled direct comparisons on the engagement levels of both cohorts. Results established interaction analysis as an approach to detect user behaviour(s), observing the degree older users failure to return and maintain activity as significant; however, users who do engage, maintain activity with a broad range of functions. Results quantified the interactions and behaviours of two disparate cohorts, determining their key user characteristics.Keywords: online social networks; interaction analysis; older users; younger users.Reference to this paper should be made as follows: Quinn, D., Chen, L. and Mulvenna, M. (2013)
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