Monetizing Social Networking

This innovative use of social networking could have a short-term payoff. It turns out to be one of the few successes to date in making money from social networking. When I ran a straw poll on making money from social networking with some software engineers, wannabe entrepeneurs and friends, they all came up with essentially the same idea: Mining the users' personal details and finding some way to make them pay to keep this information confidential. This is outside the ethical bounds of this blog so I am forced to look elsewhere for this post.

Here are some ideas. Many social networks are forums for dating or job searching so an obvious angle is to provide tools that help users in these pursuits. The drawbacks to this approach are

• it is obvious so there will be many competitors
• people don't like to stalked by unwelcome suiters or harassed by recruiters

Possible solutions are to

1. Match people. Find compatible dating partners or employee/employer matches. This suffers from being obvious but it may be difficult enough to deter competitors
2. Help people be found by the type of people they want to find them. This is a variation on 1.
3. Lower people's resistance to being matched.

Anatomy of a Relationship
Relationships with spouses, friends, employers and employees are equilibrium states. Relationships are likely to persist because of

1. Emotional attachment to current partner *
2. Financial cost of breaking relationship *
3. Irrational fear of change
4. Rational risk of change. This includes limited ability to evaluate the new partner
5. Difficulty of finding a new partner
6. Cost of learning the skills needed for the new partnership
7. Inablity to be productive while learning
8. (Current) lack of suitable partners
9. Inability to find a good match
10. Cost of relocation

Some people are not in relationships. The main groups are single people searching for partners and unemployed people searching for jobs. The * items do not apply to these groups
Helping people find partners = finding a partner for whom these barriers are low
Matching partners = is finding pair for whom these barriers are mutually low. It is not clear what mutually low means yet.
Lowering resistance to change = lowering a subset of these barriers.

Bad Strategies

1. Trying to appear what one is not. Copying other people's witty profiles, faking work history and qualifications are strategies that suffer from being easy to replicate, focusing on the means (getting a date/interview) rather the end (getting a sustainable relationship/job) and high risk/reward ratio.
2. Dating/job search advice. Many companies already provide these services. This can also suffer from focusing on the means rather than the end.
3. Competitive analysis. Competition is not the main driving force in the creation of relationships though we tend to focus on it. Monogamy, trust and reliability dominate the relationship sphere. Any winning strategy must embrace these forces.

Remaining Strategies

1. Apply actuarial prediction to people's profiles and social graphs to reveal things about them that they do not know themselves. Use these predictions to provide the matching and introductions services that are currently based on raw profile data. The tools listed on Ian Ayers' web site give an indication of what can be predicted. E.g. Probability of divorce on a given year, income 10 years from now, date of death.
2. Use the stategies from 1 for predictive health care maintenance. Monitor user data to predict disease and injury.
   

REFERENCES
Social Networking Usage
http://blog.compete.com/2007/09/14/facebook-activity-breakdown-application/
http://valleywag.com/tech/advertising/facebook-consistently-the-worst-performing-site-242234.php

Information Mining - The Social Graph

My Way Business The Social Graph: Issues and Strategies in 2008 is an enlightening overview of the social graph.

http://apps.facebook.com/socialistics/ attempts to map social graphs in facebook. When I ran it on myself http://www.facebook.com/profile.php?id=504949372&hiq=peter%2Cwilliams it did not reveal any insights I was not currently aware of. Whether this was due to the weakness analytics in the app or the lack of information in facebook links or my own lack of ability at using the app was not clear.