There is no excuse to not tracking the actions of your audience when it comes to digital media and political campaigns. From incredibly expensive presidential contests to a local school board race, political campaigns have a proven track record of using data to target voters in hopes of identifying supporters and getting out the vote when it counts. However, the pursuit of information about voters cannot stop where the analog world ends. As voters increasingly turn to the Internet to find information about politics and discuss it, they create a rich digital profile which campaigns can begin to mine for insights into their political identity.
Beyond data extraction geared towards a conventional get out the vote (GOTV) effort, namely addresses and phone numbers, new facets of a voter’s online identity can begin to be deconstructed.
No longer do voters and potential supporters need to be viewed in isolation, rather they can be placed in an appropriate social context. An examination of supporters and social media networks invites new measurements and rubrics by which to analyze influence and relevance. Robert Hanneman identifies that power in a network is relational. A voter with 10 followers on Twitter or 20 Facebook friends has less power and less reach than a voter with 1,000 followers and 2,000 Facebook friends. At its most basic level, identifying prominent members of a digital network relies on degree centrality. This form of centrality is a measurement of the number of ties an individual has to the network as a whole. The voter with 1,000 followers on Twitter has 100 the number of ties the voter with only 10 does.
A voter with a high degree of centrality in a digital network has a higher degree of influence than a voter that has a low degree of centrality. Programs that measure and visualize a voter’s centrality allow campaigns to quickly and visually identify prominent supporters that can magnify their reach through digital media. NodeXL is a program built into Excel Spreadsheets. The program recently featured a new plug in that enables Twitter accounts, Facebook profiles, and Facebook pages to be uploaded and analyzed using Social Network Analysis.
The program allows for easy to use outputs that can be used for the identification and targeting of voters on the Internet via digital and social media in the hopes of spreading the campaigns message that much further.
The graph above is a visualization of 1,000 Twitter handles whose tweets included the phrase Pink Slime, or a meat by-product that has come under particularly harsh scrutiny lately. The visualization tracks Twitter handles that follow each other, tweet at each other, and reply to each other. Granted, it can be an overwhelming site at first glance. The cascading lines in seemingly every direction, the different colored communities densely clustered together, the different variations of keywords and #’s that define each community. But clarity does come.
These sorts of exercises are crucial for a campaign above and beyond the raw extraction of data can be harvested from Facebook Likes and Twitter followers. Prominent members of a digital network that are identified by their centrality can function as new entry points to uncharted networks of potential supporters or donors. Voters that may not have been able to be linked in the past can now be quickly identified as friends using programs like NodeXL and SNA techniques to be more effectively marketed towards.
What does the future hold for digital media and politics? The sky is the limit as we set to work each and every day creating thickly descriptive personal profiles through our actions on the Internet. Whether campaigns pursue SNA based strategies to target us, identify personal influencers in our life, and target us beyond our doorstep and landline will be decided in the months ahead.
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