One of the deliverables for this research will be a Powerpoint Slide deck outlining descriptions of each of the analytical techniques described in Heuer’s 2011’s textbook “Structured Analytic Techniques for Intelligence Analysis”. The slides will also describe how the techniques can be used with social media data.
I began the slide deck by reading about the role of an intelligence analyst and the purpose of their job
Before looking at social media data, understanding the taxonomy of data is also an essential component to problem.
In addition I met with a colleague to discuss how Twitter data is extracted from a search and what programming tools and techniques he uses to analyze the data. He mentioned using the R programming language, Yahoo! Pipeline, 140 Dev for free sourcecode APIs, D3, CRAN and WEKA. Quite a bit of metadata can be extracted from Twitter data such as: user ID, the text from the tweet, re-tweets, IP address, hashtags, mentions, date/time stamp, device, and even URLs. We discussed what visualization tools he is familiar with using. In my previous Directed Field Work in the Summer of 2013, I had used a couple of in-house PNNL visualization tools (IN-SPIRE and Starlight), IBM’s Analyst Notebook, and Tableau Software to visualize social media data. At the time just visualizing the data is one thing, extracting out interesting relationships, trends and discovering a story from the data is where analysis comes into play.