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Human Dependency on various Social/Networking Systems

1,131 bytes removed, 16:26, 15 November 2010
→‎Research Notes
= Research Notes =
Introduction
 
(Source:
'''Structure and evolution of online social networks'''
http://lcweb.senecac.on.ca:2126/citation.cfm?id=1150476&dl=GUIDE&coll=GUIDE&CFID=106057593&CFTOKEN=91510606
)
* It turns out that the density of social networks as a function of time is non-monotone.
* Does a user interact evenly or lopsidedly with friends?
 
* A node represents a user and a directed edge a comments from a user to another. We call this network an activity network.
 
* Structural characteristics of the activity network has been analyzed and compared them with the friends network.
 
* Though the activity network is weighted and directed, its structure is similar to the friend relationship network.
 
* It is reported that the in-degree and out-degree distributions are close to each other and the social interaction through the guestbook is highly reciprocated.
 
* When we consider only those links in the activity network that are reciprocated, the degree correlation distribution exhibits much more pronounced assortativity than the friends network and places it close to known social networks.
 
* The k-core analysis gives yet another corroborating evidence that the friends network deviates from the known social network and has an unusually large number of highly connected cores.
 
* Its been delved into the weighted and directed nature of the activity network, and investigated the reciprocity, disparity, and network motifs.
* It has been also observed that peer pressure to stay active online stops building up beyond a certain number of friends.
http://lcweb.senecac.on.ca:2126/citation.cfmid=1460563.1460627&coll=ACM&dl=ACM&CFID=106057593&CFTOKEN=91510606
 
<u>'''Information'''</u>
Many organizations today have blogging systems, wikis, forums, and even social bookmarking and social networking services behind the firewall.
 
'''<u>Pros</u>'''
Systems like blogs, wikis, forums, social bookmarking, or social networking services, expose a lot of social network information, which is public in its nature. For example, in many blog systems, everyone may see who makes comments to whom; in many wiki systems, everyone can see who edits the same pages; in many social bookmarking systems, everyone can see who bookmarks the same web pages or uses the same tags; and in many social networking sites, everyone can see by default who is friends with whom. Thus, social applications such as those mentioned above provide a wide range of public sources for social network information.
<u>'''Cons'''</u>
Having more and more valuable public sources for social network information, both on the internet and on the intranet, presents an opportunity to collect social network information in a way that is less sensitive privacy-wise.
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