Using social network analysis of human aspects for online social network software: a design methodology

Author:

Ghafoor Faiza,Niazi Muaz A.

Abstract

Abstract Background Online social networks share similar topological characteristics as real-world social networks. Many studies have been conducted to analyze the online social networks, but it is difficult to link human interests with social network software design. Purpose The goal of this work is to propose a methodology involving the analysis of human interactions for use in designing online social network software. Methods We propose a novel use of social network analysis techniques to elicit requirements in order to design better  online Social network-based software. The validation  case study involved the collection of real-world data by means of a questionnaire to perform a network design construction and analysis. The key idea is to examine social network to  help in the identification of  behaviors and interests of people for better software requirements elicitation. Results The validation case study demonstrates how unexpected centrality measures can emerge in real world networks. Our case study can thus conducted as a baseline for better requirement elicitation studies for online social network software design. This work also indicates how sociometric methods may be used to analyze any social domain as a possible standard practice in online social network software design. Overall, the study proved the effectiveness of the proposed novel methodology for the design of online social network software.  The methodology specifically improves upon traditional methods for software design by involving social network modeling and analysis to first study the behavior and elicit requirements to develop more resilient online social network sites.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Modelling and Simulation

Reference33 articles.

1. Batool K, and Niazi MA (2014) Towards a methodology for validation of centrality measures in complex networks. PloS one 9(4):e90283

2. Blansky D, Kavanaugh C, Boothroyd C, Benson B, Gallagher J, Endress J, Sayama H (2013) Spread of academic success in a high school social network. PloS ONE 8(2):e55944

3. Bonacich P (1972) Factoring and weighting approaches to status scores and clique identification. J Math Soc 2(1):113–120

4. Bonchi F, Castillo C, Gionis A, Jaimes A (2011) Social network analysis and mining for business applications. ACM Trans Intell Syst Technol (TIST) 2(3):22

5. Boudin F (2013) A comparison of centrality measures for graph-based keyphrase extraction. In: International Joint Conference on Natural Language Processing (IJCNLP), p 834–838

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3