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Ego-Networks. Analysis and Techniques. Ego-Networks. Social Relations. Characteristics of Ego Networks. Homophily (i.e ., " love of the same ") is the tendency of individuals to associate and bond with similar others .
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Ego-Networks Analysis and Techniques
Characteristics of Ego Networks • Homophily (i.e., "love of the same") is the tendency of individuals to associate and bond with similar others. • The presence of homophily has been discovered in a vast array of network studies. For example: people have strongest ties with people who similar to themselves on key attributes, such as social calss, age sex, race, political views etc. • Heterophily, or love of the different, is the tendency of individuals to collect in diverse groups; it is the opposite of Homophily. • Heterophilyis notable in successful organizations, where the resulting diversity of ideas is thought to promote an innovative environment. Recently it has become an area of social network analysis. • Heterophily is particularly relevant for enterpreneurs. • Granovetter believes that weak ties provide people with access to novel information.
Characteristics of Ego-Network Social Networks
Visualizing or Analyzing your own Networks on facebook or Twitter using freely available tools • Touch graph: you can visualize your network, examine friend ranks, friend’s position in the network, weak and strong ties and overall structure of your Ego-Network. • Node XL: It imports data from Twitter, YouTube, Flicker and Your E-mail Client). Note: It can be downloaded from http://nodexl.codeplex.com/releases/view/40939 • Pajek (Windows, free). • Netdraw (Windows, free). • Mage (Windows, free). • GUESS (all platforms, free and open source). • R-Package for SNA (all platforms, free and open source).
References • Community Detection and Mining in Social Media. Lei Tang and Huan Liu, Morgan & Claypool, September, 2010. • C. C. Aggarwal (ed.), Social Network Data Analytics, DOI 10.1007/978-1-4419-8462-3_1, Springer Science+Business Media, LLC 2011. • Linton Freeman, The Development of Social Network Analysis. Vancouver: Empirical Press, 2006.