ForwardTrack

ForwardTrack is an open source tool (now entirely written in php) that allows email campaigns to be tracked and mapped as they are forwarded from person to person. This is definitely useful as it reveals the spread of information and some of the underlying social network.

Political Campaign Contributions

The Federal Election Commission (FEC) requires that all campaign contributions over $200 (per donor) be reported publicly. The reported information includes the donor's name, job title, zip code, and even address. All of it, since 2001 is available electronically via FTP at ftp://ftp.fec.gov/FEC/electronic/.

In collaboration with Political Scientists here at BYU we have been performing record linkage (aka. entity resolution) on this data, so that they will be able to more accurately perform their studies.

Fundrace
On a related note, fundrace.org has created an interesting mashup (shown below) that maps donors on a Google map colored by the party or candidate donated to. It also, reveals donor information and appears do do some coarse record linkage.


FEC Maps
Additionally, the FEC itself has started to produce maps both for the Presidential Election and House and Senate Elections.  The maps they provide aggregate the donated funds by state, party, and candidate.

Duncan Watts Downplays Viral Marketing Hype

A while back I quickly saw Clive Thompson's article entitled Is the Tipping Point Toast?, but didn't have the time to read it all nor investigate it any further --- until today.

Thompson's article pits Malcolm Gladwell's thesis (in The Tipping Point) against the recent research of Duncan Watts (cited below). I thought the article was well-written and adequately presented both sides of the issue. In short, Watt's claims that spending time and money marketing to influential individuals is no better than marketing to the masses.

Through all of this, Watts makes some important points such as (quoted from Thompson's article):

• The problem of popular viral marketing talk is that it is "incredibly vague"; "how an influential actually influences is not explained." "Precision matters when trying to explain highly social epidemics"
  
• "Influentials don't govern person-to-person communication. We all do."
  "Common sense is misleading"
• Thompson writes that Watts found the "rank-and-file citizen [to be] far more likely to start a contagion"

So, today I finally took the time to learn more about Watts' recent research, available at Collective Dynamics Group website (at Columbia University) as a Working paper in the Papers section. Through the years, I had previously read some of Watts' work, so I was excited to see his recent findings. In this paper he presents an approach they call "Big Seed Marketing", which in essence combines a traditional mass marketing model with a viral propagation.

The idea that there is "no free lunch" in viral marketing is useful to point out, as "there are many more unsuccessful attempts that one never hears about." He also, points out that it is "hard, if not impossible" to predict which of attempts will succeed.

The take-home message in the conclusion is that effective marketing campaigns can be produced without identifying "influentials", but simply by adding a mechanism of peer-to-peer sharing to propagate the message. (As an aside, the formalism presented in the paper is useful for discussing the problem and easily evaluating the results.)

Watts makes some good points, however, I would still argue that people with high social capital (you might call "highly influential") can heighten the network effect. This is even evidenced in Duncan's paper --- as one of Tom Mauser's 'friend' was StopTheNRA, who, in turn sent a large email blast (Table 1, footnote 1). So, Tom Mauser, had a significant enough relationship with StopTheNRA that they used their resources (their large email list) to forward his message.

Although, there is an element of hype in the presentation of "Big Seed Marketing", I find it useful as it presents a nice way of making the issue sticky and bringing to light these more subtle points. The desired effect of propagating these ideas seems to be occurring.

Update (4/23): Podcast with Duncan Watts on Buzz Marketing (mp3)

Looking for a Job?

There are a lots of places to search for jobs online these days including:

• SimplyHired - easy to use job search
• HotJobs - Yahoo's job site
• Monster - you've probably heard of Monster
• Indeed - newer site that allows you to filter by salary (for instance, here is an example salary search on computer science and data mining)
• LinkedIn - use your social network to find your next job
• erecruiting - for new college graduates

An interesting approach to finding your next job might be to leverage your social connections to match you with a good employer with needs inline with your skills. Of course, as nice that sounds in theory, I would bet it could be challenging in practice.

Although, I won't be needing a full-time job for another couple years, it is always interesting to see what jobs are available (and what skills are in demand) by quickly searching on your skills and interests.

SIP Recap - Thursday

Here is a recap from the Social Information Processing Symposium:

1. Brian Skyrms (UCI), Signaling Games: Some Dynamics of Evolution and Learning
2. John Nicholson (USU), The Blind Leading the Blind: Toward Collaborative Online Route Information
3. Cosma Shalizi (CMU), Social Media as Windows on the Social Life of the Mind
4. Gustavo Glusman (Systems Biologist), Users, photos, groups, words: Analyzing mixed networks on Flickr
   
5. Luc Steels (Vrije U), Social tagging in community memories
6. Aram Galstyan (USC/ISI), Influence Propagation in Modular Networks
7. Adam Anthony (UMBC), Generative Models for Clustering: The Next Generation
8. Peter Pirolli (PARC), A Probabilistic Model of Semantics in Social Information Foraging
9. Hak-Lae Kim (DERI), int.ere.st: Building a Tag Sharing Service with the SCOT Ontology
10. Yu Zhang (Zhejiang U), Mining Target Marketing Groups From Users' Web of Trust on Epinions
11. Andrei Broder (Yahoo), Reviewing the Reviewers: Characerizing Biases and Competencies using Socially Meaningful Attributes (see Sihem Amer-Yahia)
    

The Wednesday talks were excellent. In particular, I really enjoyed:

• The subtleties of the blind leading the blind (see 2 above)
  
• Gustavo's unique way of analyzing Flickr relationships (see 4)
• Adam Anthony's overview of generative models that can be used in clustering (see 7)
• Pirolli's analysis of Lostpedia using LDA (see 8)
  
• Hak-Lae Kim's tag aggregator application (see 9)
• The use of socially meaningful attributes as presented by Yahoo's Andrei Broder (see 11)
  

Freemium Business Model

The freemium model is something that I've been telling start-up businesses to do for quite a while. It allows community --- where social capital resides --- to build around your service at a fundamental level. After a captive community has been established, premium features (or services) can be offered, which effectively converts social capital into profit.