Open Journalism & the Open Web

"Does the above make sense?

Seems like a good fit with the assignment, and last week's lecture. :)

Phillip.

I like this idea a lot. Here is something that might be interesting. Truthy.com (from Indiana U.) Here's what they say: "... Truthy is a system to analyze and visualize the diffusion of information on Twitter. The Truthy system evaluates thousands of tweets an hour to identify new and emerging bursts of activity around memes of various flavors. The data and statistics provided by Truthy are designed to aid in the study of social epidemics: How do memes propagate through the Twittersphere? What causes a burst of popularity?

We also plan to use Truthy to detect political smears, astroturfing, misinformation, and other social pollution. While the vast majority of memes arise in a perfectly organic manner, driven by the complex mechanisms of life on the Web, some are engineered by the shady machinery of high-profile congressional campaigns. Truthy uses a sophisticated combination of text and data mining, social network analysis, and complex networks models. To train our algorithms, we leverage crowdsourcing: we rely on users like you to flag injections of forged grass-roots activity. Therefore, click on the Truthy button when you see a suspicious meme!
System Architecture

Streaming Twitter data is acquired in real-time from the 'Gardenhose'. We match all tweets against a set of keywords to exclude tweets unlikely to contain political discussion, and extract all memes (@mentions, #hash_tags, and urls). We further isolate memes of interest by considering only those memes that have just undergone significant changes in volume, or those that account for a significant portion of the total volume (but perhaps haven't fluctuated very much). We insert these memes in the database, and use the Twitter API to get more information on each. ..." More here: http://truthy.indiana.edu/about