Friendster and Publicly Articulated Social Networking, A Social Network Caught in the Web

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Friendster and Publicly

Articulated Social Networking,

A Social Network Caught in the Web

By: Mitch Lederman

Date:4/12/07

Shivnath Babu

What is Friendster?

• 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.

Friendster’s major growth

• 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

The value of the network

• 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

Problems cont…

• 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.

Presentation of self

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

Friendster as a site of connection

• 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

Dating 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.

Fakesters

• “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”

Fakester Dilemma

• 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?

Learning from Friendster

• Major problem around publicly articulated information

• Reshaped how groups of people verbally identify relationships

• Importance of creative play in social interaction

Club Nexus

• 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

User registration and data

• 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

Network Analysis

• 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?

Properties of individual profiles

• 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

Properties of individual profiles cont.

• 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

Association by similarity

• 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.

Nexus Karma

• 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 does this relate to Google?

• 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.

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