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

1. Friendster and Publicly Articulated Social Networking,A Social Network Caught in the Web By: Mitch Lederman Date:4/12/07 Shivnath Babu

2. 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.

3. 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

4. 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

5. 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.

6. 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

7. 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

8. 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.

9. 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”

10. 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?

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

12. 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

13. User registration and data • 1st step-enter name, e-mail addresses, birthdays, major, year in school, home country and state, phone number-etc. • 2nd step-users asked to list their friends at Stanford- “buddies” • 3rd step-list interests and hobbies • 4th 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

14. 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 unevenly- most 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?

15. 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

16. 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

17. 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.

18. 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

19. 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.