By: Mitch Lederman
Date:4/12/07
Shivnath Babu

• Friendster
– Its an online dating site utilizing social networks to encourage friend-of-friend connections.
– Built under the assumption that friends-of-friends are more likely to be good dates than strangers
– Built to compete with Match.com
– Friendster only allows you to access those friends with four degrees
– Friendster encourages users to join even if they are not looking for a dates, under the assumption that they know a wide variety of friends who are looking and would serve as a connecter and recommender.

• Launched its public beta in the fall of 2002
– As of early January 2004, the site is still in beta and has amassed over five million registered accounts and is still growing

• Friendster assumes that users will define their identity by their profile to ensure meaningful connections.
– The users will see the value in connecting to actual friends.
– Is the value of the network good?
• Many Problems?
– Friendster fails to recognize that publicly articulated social networks and identities are not identical to the private articulation.
• Public identities are not the same as private ones

• Relationship indicators in Friendster are binary: Friend or not
– No way to tell what the weight of the relationship is. Some list anyone as friends, some stick to a conservative definition, most list anyone they know and don’t dislike.
– This means that people indicated as Friends even though the user does not know or trust them
• Because of this weakness, the weight of a friend connection is often devalued because trust cannot be guaranteed.
• Publicly articulated social networks disempower the person performing.

• Friendster Profile (Presenting themselves based on specific time and audience)
– Demographic information
– Interest and self-description
– Pictures
– Friend listings
– Testimonials
• Context is missing
– Individual is constructing a profile for a potential date and also one must consider all the friends, colleagues, or other relations who might appear on the site.
– Social Appropriateness
• Truth
– One is simply performing for the public, but in doing so, one obfuscates quirks that often make one interesting to a potential suitor.
• Making it so confusing as to be difficult to understand behaviors that make one interest
• Teachers fear the presence of their students on Friendster
– Everyday activity we present different information depending on audience

• People use Friendster to connect to others for a variety of reasons.
– Connect with people that they know, reconnect with long lost friends, and colleagues. (Individual connections)
– Private elite clubs and pub gatherings
– Memorials
– Communication
– Auctioning connections on EBay
– Women advertise their porn sites by attracting potential clients
– Fraudster profiles to deal drugs, using the bulletin board to announce events
– Many are using Friendster for its intended purpose: dating.
• Dating falls into three categories

• Hookups
– Three to four degrees away
• Direct Pestering
– Look at friends’ friends and bug the intermediary about potential compatibility.
• Familiar Strangers
– Strangers that one sees regularly but never connects with.
– Browsing site, users find people they often see out and look at their profile.
– Then by that, they can send them a message or approach offline.

• “Fake Personas”
• Three forms of Fakesters
– Cultural characters that represent shared reference points with which people can connect (God, George
Bush, Tim McGraw)
– Community characters that represent external collections of people to help congregate known groups (Duke University, San Francisco, Burning
Man)
– Passing characters meant to be perceived as real
(duplicates of people on the system)
• Fake female character
• “Fraudsters”

• Company has never approved of this behavior
(collapse network &devalue meaning of connections between people)
• Most people love fakesters
• Tension between company and users
• Company outraged users by deleting fake profiles
– “Fakester Revolution”
– Site became less interesting when Fakesters removed
– Is anything actually real on friendster?

• Major problem around publicly articulated information
• Reshaped how groups of people verbally identify relationships
• Importance of creative play in social interaction

• Stanford in the fall of 2001, reflection of the real world community structure
• System to serve communication needs of
Stanford online community
• Send e-mail and invitations, chat, post events, buy and sell used goods, and search for people with similar interests.
• Attracted over 2,000 students early on.
• How they connect people

• 1 st step-enter name, e-mail addresses, birthdays, major, year in school, home country and state, phone number-etc.
• 2 nd step-users asked to list their friends at
Stanford“buddies”
• 3 rd step-list interests and hobbies
• 4 th step-select adjectives to describe personalities, what they look for in friendship-etc.
• Using data, they were able to deduce attributes contributing to the formation of friendships

• Nexus Net-large social network with 2,469 users and
10,119 links between them.
• Number of buddies a user has is distributed unevenlymost users had just one buddy, some had dozens of friends, and one had more than a hundred.
• Small world effect-
– distance between two users, measured in number of hops along the Nexus Net is only four on average.
• Counterintuitive aspect: people tend to socialize in smaller cliques, yet they are separated by only a small number of hops.
• Separated/far away/not connected to many other people because in a small clique.
– How can be separated by only a small distance?

• Z-score- (number observed)-(number expected)/(standard deviation)
– Used z-scores to characterize the relationship between different attributes the users chose. Also, they indicate how likely it is to find a connection between two attributes by chance.
• Ex-Funny and enjoy watching comedies
• Personality and preferences (factors influencing friendships)
– Used this analysis to find correlations between users personalities and preferences.
– Described attractive=appearance is important
– Described funny=sought laughter in relationships
– Described weird= weird friends, spend time alone and at home
– Described successful- activities, fulfilling commitments
• Homophily

• Academic major and personality
– Examined relationship between persons academic major and what adjectives they chose to describe themselves
• Physics, math, engineer majors-nerdy stereotype, learning, weird. English majors-reading. Undeclared-doing anything exciting
• Gender differences
– Examined how gender influences personality and preferences.
• Men-Football, war movies, sex, activities
• Women-gymnastics, romance movies, trust, socialize

• Tendency of individuals sharing interests to associate with one another
• Activities or interests shared by smaller subset of people showed stronger association ratios than very generic activities that could be enjoyed by many.
– Ballroom dancing vs. partying
– Duke Football vs. Football
• Similarity and distance
– Similarity with a friend decreases as distance between users increases
– Higher likelihood we share a characteristic with a friends’ friend than we share it with someone four hops away.

• By e-mail as a new feature-users who were ranked by three buddies were sent an e-mail to do the same.
• Users could rank how trusty, nice, sexy, and cool their buddies were.
– Some variably in scores given
• Demonstrates a clear correspondence between the way that individuals perceive themselves and the way that they are perceived by others.
– Described responsible-received higher trusty scores
– Described attractive-higher sexy scores

• How we interact with people socially on the social networks has a lot of information.
– Profiles
– Registration
– Friends
– Pictures
• Google=make worlds information accessible.
• Need to improve indexing and storing for all this information (not indexing images of me on facebook nor my information)-Google desktop is helping
• Study on Club Nexus done by Orkut Buyukkokten helped him start Orkut.com
, which is a social network associated with Google.