This post is still under development. Really, it’s a mess. Just making it public so I don’t have to log in to read and think about it.
Finally! My amateur information studies and current affairs interest collide. I am fascinated by a recent meeting of China’s Minister for National Defense Liang Guanglie and the United States Secretary of Defense Leon Panetta. So much so that I’d like to take this opportunity to analyze the event using some OSINT and some ideas that I’ve been toying with.
The information that I’d like to focus on–the primary information–revolves around the specific discussion of internet-based threats between the two countries. There are many genuine news articles covering Guanglie’s visit, many of which simply reiterate the same information, but there are less that concentrate on cyber defense issues.
- Collect related OSINT and define the primary information and information sub-classifications
- Graph on a 2-dimensional ERD the four preidentified “dimensions” (analysis of each dimension should output their own unique data)
- The people and organizations that the news media is about and their relationships (focus: classifications I-V)
- The people and organizations that document and process the information shared by ‘2A’ and their relationships (focus: classifications II-V)
- The information that ‘2B’ shares and the relationships between information for a single news article (focus: classifications I-V)
- The information that ‘2B’ shares and the relationships between information between all articles concerning the predefined primary information (focus: classifications I-V)
- Describe the relationships via information classification normalization (focus: dimension 2C and 2D), or, in other words, juxtapose all four dimensions
- To describe, as holistically as possible using internet-based media, the public’s theoretical whole-view of the event.
- I’m actually going to limit myself on the number of information sources that I use since none of this is automated and it is all very theoretical. Ideally, an automated system, such as new functionality built into Google News, would be able to process all indexed articles on the web.
Classification I (primary) sources:
Raw txt: http://anon.is/raw1.txt
Classification II-V sources:
- Are we, as information consumers on the net, just supposed to assume that the primary information is the condensed subject matter in an article’s title?
- Are we to presume that the author is aware?
- Why is information not clearly identified via classification or relationship description?
- The net provides vast OSINT. Why do news media organizations limit themselves by pulling targeted information out of other information sources?
- Why are those sources, at times, not hyperlinked?
- Why don’t said organizations design information gathering systems (#bigdata) to provide seamless information traversal using smart UX?
– Some do minor historical analysis and even less do trend analysis.
Information producer takeaways:
Information consumer takeaways: