In this project I analyzed how the news outlets were treating the 2008 presidential election through their use of headlines and titles. As a consumer of news through Internet and TV media sources, I realize how important titles are in catching the attention of potential readers and watchers. I also realize that, depending on the names they throw into its titles, a newspaper caters to a certain population and makes an editorial, and somewhat questionable, choice to bias its point of view. For this project, I targeted some of the largest newspapers in the US (New York Times, Washington Post, and the BBC, as the lone outsider) to determine whether or not at any moment they were catering to the readers for profit, or were catering to a fair and balanced view of the proceeding election. In a sense my program could be considered a media watchdog.

How to visualize a newspaper's slant, though, is quite difficult given only shapes and colors. I chose initially to have a matrix of 16 squares (4 x 4), in which each square represents a news article's title. The titles were gathered through the sites' XML feeds, and I received 16 titles for each paper. If the title contained certain words pertaining to either the Democrat or Republican parties, the square would either be colored blue or red, respectively. As a representation, this was sufficient to underline how much a certain candidate or party was being talked about in that particular news outlet, but the method only went so far. For example, the New York Times, a traditionally liberal paper, could have many more red squares than, say, the Washington Post, a traditionally conservative paper, but only because the paper would be highlighting negative stories about the Republican candidates. Would it be accurate to say the New York Times is a conservative paper based on the coloration of the tiles?

I then wanted to introduce the titles themselves as part of the visualization. It was, admittedly, a lazy decision on my part, as usually you want to direct what the viewer sees rather than dump unfiltered data on them. But given that the titles would be projected onto the colored tiles, I feel that the user was given a binary choice rather than a bunch of colored squares and a bunch of titles: did the title and tile match up, or did they contrast? In other words, the title was to be used as a way for the user to decide if the tile's color meant the paper was covering that candidate to entice readers or incite them (and in a sense, both of these are business decisions). At this point, I also introduced the purple square, a convergence of both viewpoints, both Republican and Democrat; in my mind, a newspaper with mostly purple squares showed a more comparative, critical and astute view of the election, without regard to profitability or favoritism.

The results? Well, the Washington Post proves to be continually conservative, the BBC tended to place interest stories above critical political stories as seen by the titles, and the New York Times did a great job in portraying both sides equally and almost always had the highest number of purple tiles.

Once I made my conclusions about these news sources, I wanted to include a bit more interactivity to the program, and made each cube a link to that news story's site. The project gained an added feature: as well as being a watchdog of sorts, it also provided the user a way to actually get to the content itself and judge the story from that angle as well. This component of my midterm was the most interesting to me, as my background is in web and knowledge management. The biggest step in providing a user experience is not deciding how to present data to the user, but how to get them to interact with it, and given this functionality users not only consume the data as I present it to them, but can also interject and give themselves access to the stories available.