Scalamoondis

If you are anything like me, you’d like to believe that your own taste in media consumption and its accompanied habits is a little more sophisticated and nuanced than the average person. Whether through the actual topics visited or the time spent consuming, I believed that I would set myself aside in one way or another. Well, that was not the case. After analyzing and categorizing my media over the last seven days, I believe anyone would classify my media consumption as impeccably average to the demographic of a college student.

Analyzing the media we visit, and the frequency of those different types of media, can be incredibly valuable on many different fronts, for example, introspection or marketing. Depending on the depth of analysis, having the opportunity to see what kind of media catches and keeps your attention can give you insights into the keywords and patterns that work for people like yourself. If I wanted to make some kind of media for a college student of a particular major, I could analyze similar popular media tastes of my own to get another kind of data point towards the target design of my media creation! There is also the option that you just want a more concrete picture of what is taking up your time inside the media sphere to ask questions like: am I spending too much time on entertainment sources, or do I consume enough educational and informative media to secure success in my academic endeavors? Researching the answers to these questions can help organize your schedule to better account for where and how you want to spend your digital allowance, regardless of whether it’s in the entertainment or educational sector.

Fortunately, enough for my case, the way my data was patterned allowed the methodology behind logging my media consumption to be pretty straightforward and self-explanatory. I gathered data from my computer from the past seven days to give a large enough sample in the hopes of catching enough patterns and anomalies to make things interesting. I figured about ninety percent of my history would be academically correlated, so including the weekends where I’ll have a little time to play games or watch a few YouTube videos would give a more accurate representation of my general consumption habits. I then listed what platform the media was found on; by platform I mean the websites like Google, YouTube, or the domain that contains the media. Differentiating the platform fluidly leads into listing the actual title of the content or the search that contained the content I viewed. My next step was where things actually started getting placed into bins and boxes: I started listing what type of content the entries were. The types of content could be educational, informative, entertainment, classwork, shopping, etc. Next, I began to gather the entries into the format they took like text, video, or slideshows. The purpose or the motivation behind visiting the different media was another category I used, this category often followed the same descriptors as the type of content. After purpose, I labeled what kind of engagement I was giving towards the media. If I was actively interacting with it, it was assigned the label active, otherwise it’s passive. Lastly, I reflected and gave a brief explanation as to why I was arriving at some of the entries. I offered descriptions like if it was for classwork or homework, was it entertainment, or what about the media keeps my attention.

As I stated at the beginning, the results would not come as a surprise to most people after understanding my demographic. However, as I also stated at the beginning, there really isn’t any hard anomalies that could sort of develop into a pattern itself, that I believe would set me apart from the norm. For example, I would like to believe that every swamped college student has some kind of specific media consumption outside their usual forms of entertainment; mine being technology and science topics. One significant data point I would like to add that didn’t fit into the way my data was collected is my Film and TV consumption. For over the past eight or so years, I’ve watched at least one episode or a movie almost every night with my friends. If I go to bed late, then it’s usually an hour of a show, otherwise I opt for a movie almost every time. With this key data in mind, you can imagine how it could possibly skew the representation in the pie chart, but the other forms of media can be visited over multiple times a day. This is where the drawbacks of the methods behind your data collection come into play, so it’s important to critically pick how you analyze your own consumption.

^ This is the excel data used in my analysis.

^ Here is my Team’s group presentation and analysis!