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Build a Voter File with FaceBook

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Why Build a Voter File?

[[http://en.wikipedia.org/wiki/Voter_file|Voter Files]] are used to identify potential supporters in your local area, sift out voters more likely to support your opponent, and maximize the effectiveness of Get Out The Vote (GOTV) and awareness raising campaigns.

Building and maintaining and an accurate voter file will increase the effectiveness off your campaign, save you time and energy, and help you identify and build support for future campaigns.

Problems with Voter Files and Campus Activism

College kids are a transitory bunch. We change addresses just about every year, we may be registered in our home state rather than the state in which we attend school, and frequently we don’t have landlines. It makes it hard for local campaigns, state party activists, and even our own campus activists, to efficiently rally us around a cause or turn us out during an election. It also means that the state party’s voter file for young voters is basically useless (that is, if you can even get your hands on it). Clearly, if we’re going to GOTV our peers on campus, we need a new method.

The Solution: FaceBook, Your Campus Registry, Some Elbowgrease

With a FaceBook account, access to your student registry, and some time, you can build your own voter file that will blow away anything the state party can give you. Here’s how you do it:

  1. Sign up for FaceBook and join your campus network.
  2. Perform an advanced search within your campus network to identify your fellow students and categorize them by their political persuasions (Very liberal, liberal, moderate, conservative, very conservative, apathetic).
  3. Copy their name and political viewpoints into Excel.
  4. Get a copy of your campus registry - online, if possible. This will contain the names, addresses, and phone numbers of all the students at your university.
  5. If you have an electronic version of the registry, dump this into your Excel document, making sure that the first and last names from the registry occupy the same columns as your data from FaceBook (ie all last names from both data sources in column A, all first names in column B) . If you don’t have an electronic version, you’ll have to enter the registry data by hand - a daunting task that will take a lot of man-hours. If this is the case, start by looking up your most hardcore supporters first (those who self identify as “Very Liberal,”) and work your way down the list to less politically intense students.
  6. Sort your data by last name (alphabetical).
  7. The name/address data from the registry should now match up with the name/political persuasion data from FaceBook. Merge the data as best you can. You can remove Republicans (cut and paste them into a new Excel doc. You never know when this data might come in handy).
  8. Prioritize the names. People who are very liberal are your “1’s” in political speak - your most hardcore supporters. Next are those who identify as liberals, followed by moderates, then those who are apathetic.
  9. You will most likely be left with a lot of names that have no political correlation. What can I say - not everyone is on the FaceBook. These are you “undetermineds.” Hopefully you will have removed a lot of Republicans from this list (this is why we searched for data on people of all political persuasions. Undetermined students are of a lower priority in your activities than those who self identify as Very Liberal or Liberal (or even Moderate), but they are another pool of potential supporters.

And there you go - an accurate, and easily updated campus voter file. Now it’s time to start reaching out to those potential supporters.

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March 22nd, 2007 5:36am
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I'm in a breakout session at

Submitted by feliduca (not verified) on Tue, 2008-09-30 14:37.

I'm in a breakout session at the New Democratic Network's daylong conference on "New Tools, New Audiences," listening to Vijay Ravindran, the CTO of Catalist, talk about web 2.0 and its development of an "Enhanced Voter File." As usual, these are my rushed notes, and at best a good paraphrase of what was said, not direct quotation.

The traditional voter file, which is collected by state bodies, is just name, contact info and party registration, and past voter behavior.

The enhanced voter file, something that Democrats, Republicans and sometimes other organizations build and maintain, contains commercial data, census data, historical information about your behavior, and specialized data (like lifestyle choices). (Vijay notes, later in the Q&A, that this kind of data is often a weak indicator of people's actual political preferences, and hypothesizes that someday under an OpenID framework, campaigns or organizations like his might be more interested in highly accurate information that individuals volunteer about themselves.)

Enhanced voter files are used for canvassing, and also for modeling campaigns.

Catalist is building on the lessons of 2004 (where Democrats had a database meltdown) and working to build a 50 state national database:

Catalist's voter file has the names of 180 million registered voters, plus 75 million unregistered people (for use by voter registration groups), enhanced with commercial data, specialty data (like who owns hunting licenses), integrated it with the Democrat's VAN application, and with a tool for subscribers to mine the data.

Catalist's goal is to be a permanent piece of progressive infrastructure. Vijay talks about Tim O'Reilly's "What is Web 2.0" paper as his "baseline in driving Catalist." So he goes thru some of O'Reilly's key points about the development of web 2.0.

1. The web as a platform: Examples are Amazon, Facebook, Google. For Catalist, this means: if our data is inaccessible, it doesn't exist. (This is another reference to the Democratic data disaster of 2004.) A database administrator is a poor excuse for an interface where people can self-administer. From the very beginning, having a back end web interface was essential. We also created a web services API for progressive organizations with technical staff.

2. Harnessing collective intelligence. Examples are Wikipedia, Amazon, Flickr. For Catalist, this means storing, organizing and utilizing in perpetuity the collective personal data of its customers. It means removing the technical limitations around cooperation, building value-added meta-data that no one else can, and relying on its customers to make its data more correct. (This is sort of the open source model for bug fixing, but Catalist isn't an open product. But inside its ecosystem, it sounds like it's applying the same logic.)

3. Data is the next "Intel inside." For Catalist, this means instant access to information about nearly everyone over 18 in the US in a single format, easy upload of proprietary data for integrated data mining, giving back unique identifiers for each data point, and the creation of a proprietary matching system for the data. What this means you can combine field canvass lists, fundraising, membership, polling info and online engagement, to get a 360 degree view of people and figure out more ways to engage them (or ask them for money, he notes, if you haven't already).

4. End of the software release cycle. Examples are eBay, Netflix, who make their fixes in real time online. The same can be true for politics. Data can be updated in critical election months; no more stale data. And new features and bug fixes need to be deployed rapidly. (No more 2004 horror shows for the Democratic side, in essence. He draws a parallel to Christmas season at Amazon.)

5. Lightweight Programming Models. Examples are Amazon Web Services, YouTube's embed feature. Catalist's approach is to not try to do everything. Their web service is designed to allow other's creativity to take advantage, like MoveOn's "Vote Poke" application. Their formats are usable by microtargetters, and other groups can syndicate their data (like America Votes)

6. Software Above the Level of the Single Device. They're making application configurations for field, analytics, fundraising, strategy, pollsters. etc. Vijay mentions the need to make these more Blackberry friendly, given how many political staffers have them.

7. Rich user experiences. Catalist's Q tool has a professional UI design, maps, drag and drop crosstabls, inline updated counts and access control for organizations.

Where is this going? With more data and more collaboration, and web services, more innovative applications will get built both by Catalist and others. He sees the semantic web coming, intelligent crowd sourcing, integrated web mining...and ultimately more progressive power.

Question time. I ask about their business model. Subscriptions to Catalist are $25K to $400K per year. Several hundred organizations are clients. About 40 people on staff. 15 terabytes in size database. He analogizes it to an electric company, where no one org would ever have the wherewithal to build one, but it is essential infrastructure.

I also ask: "How do they insure that they're only selling their services to progressives?" He says they haven't hit the interesting question yet of "what if Joe Lieberman wants our services?" It would be up to the board. AARP would be considered progressive, he thinks.

In terms of how information is shared internally: A lot of nonprofits that use Catalist's data release their own results back for others to use, such as Womens Voices, Womens Vote, one of their clients. By and large, donor data, membership info tends to be kept private by clients.

A very impressive presentation. Ravindran, who left Amazon to lead Catalist's technology team, has clearly brought the wisdom of Silicon Valley to the political infrastructure business. He's definitely someone to watch.

______________________
Submited by : Libros Gratis

blog entry

Submitted by Michael Connery on Tue, 2008-09-30 15:24.

You should write this up as a blog entry so more people can read it. It's very much buried here in the comments.