Facebook Breakups Chart

Recently when I was browsing online, I came across this chart.  The graph depicts breakup frequency gathered by using data collected from Facebook relationship statuses.  The graph kind of reminds me of something like a Google Analytics graph that charts the number of visitors over time and allows you to see trends in data.

There are some very interesting features labeled on this graph.  For example, breakups are most frequent during spring break and a few weeks before Christmas.  However, Christmas Day is the lowest point on the graph.  Also, it’s really interesting to note how Monday appears to be the most popular day for break ups to occur.

I thought this graph was a unique example of how big data can be used to expose interesting information.  The production of this chart did not require any experiments or surveys, just data about relationship statuses that Facebook tracks.  On one hand, this is cool and shows some of the potential Big Data could have.  Without Big Data, this graph would have been much more difficult to produce as accurately.  Surveys would have had to be distributed to people and these people would have had to fill them out to from memory, which may not be exactly accurate.  But with this data from Facebook, it is easy to track exactly when breakups happen.

On the other hand though, it is more than a little creepy to think about how much data Facebook has and what other metrics they could track.  This example is fun and entertaining, but Facebook has so much data, you can never really know what they are keeping track of.

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6 Responses to Facebook Breakups Chart

  1. samargolis says:

    The spike on April Fools Day is interesting, some people have a hilarious sense of humor. But yes, watching someone’s relationship status is weird.

  2. hustonsa says:

    I have seen this before, I think it is an interesting graphic. The trends in break ups right before long breaks such as spring breaks and Christmas make sense when you think about it, being away from your significant other could cause stressors that are not normally seen throughout the year. However, it is interesting that similar spikes are not seen before summer, possibly because you may stay in your college towns over the summer for jobs or to take classes. Of course, I am looking at it and evaluating it from the prospective of a college student.

  3. maddiegogo says:

    This is a great example of how data that already exists can be used to find some interesting trends in society. It goes back to the whole concept that science these days in changing because instead of coming up with new experiments many scientist can look at the data already out there and analyze it in a meaningful way.

  4. mfrohman says:

    This is such an interesting graph that I know would not have been possible without the ubiquity of Big Data. Now that I think about it, without Facebook either. Facebook is the largest social networking site and according to my knowledge, the site where the most people publicly display their relationship statuses. As a result, Facebook provides the most accurate and largest quantity of data about Facebook relationship statuses. These trends would not be as accurate if the data was not gathered from such a popular site as Facebook.

    However, one thing to take into account is that all Facebook relationships are not always real. Meaning that some people “marry” their best friend from high school or become “engaged to” their good friend from last summer’s teen tour they went on. I personally was married to my best friend on Facebook for a period of time, but we were not actually in a romantic relationship. So, while these trends do seem to make sense, they could be based off of some false data.

  5. clairejwiggins says:

    Again, even though this information we gain from facebook is definitely interesting, we should draw conclusions with caution. For example, on christmas there is a very low amount of breakups, but this may be just because people are not on the internet as much on Christmas, as they may be spending more time with their families, or they might feel bad about making a negative post like that on a holiday. I would find it interesting to compare this chart of facebook breakups with a chart of facebook makeups, or the start of new relationships. I am surprised that there are such clearly defined peaks in this chart. Maybe when someone breaks up with someone else, it really “isn’t them” that is causing the problem, it is just time of year.

  6. julianami says:

    I think this is a great example of how we can use readily available data to gather information, but also a good example of how we shouldn’t draw conclusions/causation just from looking at correlations. Overall, with so much available data, it seems reasonable to draw conclusions, but at the same time, just taking a look at some of the points on the graph give us reason to doubt the accuracy of the results. For example, there is a spike in breakups right on April Fool’s day, and all that goes to show is that quite a lot of people have that in their sense of humor. Moreover, there could be reasons beyond what we see in the graphs for why people don’t break up certain times of the year. For example, Christmas is a low point for break-ups, but that could just mean people feel bad breaking up on a Holiday, or feel bad releasing such information on that day. While it’s interesting to draw conclusions from big data, we should always keep in mind that these results generally don’t show causation, but only correlation.

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