Software breaks down social media interactions into visual, but is hard to comprehend

Social network analysis software takes a specific social media platform, such as Twitter, and compiles everything posted on a specific topic into one graphic to display

Marc Smith, who helped build the program “NodeXL”, said that society loses the “crowdness” online when something important happens. He made the comparison to having everyone who posted stand in a single-file line because that's how Facebook and Twitter feeds work.

At first glance, the visual representation social network analysis software of Twitter on “NodeXL” looks like a kid who stole his parents' crayons and scribbled on the wall. It's tough to decipher what all of the lines and minuscule boxes mean.

When you examine the graph closer, for instance one Marc Smith made for Major League Baseball Twitter in a 2-hour, 26-minute span on Aug. 25, you can glean more information. In each sectioned off box, it highlights the key words that were written by users.

So in the top, most-said words are the words: mlb, baseball, new wire, card, lineup, 25, schilling and tickets. So from this, one can figure that there was some sort of significant news or talk around former pitcher Curt Schilling.

But perhaps what's most important about this graphic and the software in general is the interactions that it shows. The software is based around the mentions and replies between each box, so the skinny green lines drawn between each box show how often there were interactions between each square.

In the graphic on baseball, there are a significant amount of lines draw between the second and third box, meaning there was some sort of increased connection between the words in each. For some reason, the users in each box were more likely to be interacting with one another.

This technology seems like a great idea. With how prevalent social media has become and the way users flock to in times of breaking news, it's important to break down the single-line format to show the crowd that you can easily miss.

Unfortunately, the visual representation this program creates are more confusing than they are helpful to the average viewer. Without notable research into how to read it, it just looks like a mess. The idea behind it is great, it just seems to need more work in how it is displayed.