Aug 13, 2018

Monday Map #7: Complainers of Detroit

At some point, we've all run into an "Eeyore:" a gloomy, pessimistic person who is fixated on their problems. Their world is grey, the glass is always half empty, and nothing ever seems to go right for them. I know I've been that guy at times. 

Often, when I'm stuck in my head, someone outside my situation can clearly see that things aren't nearly as bad as they seem. Rather, if I'm being honest, I'm being a bit overdramatic and making something trivial sound apocalyptic. This is our "Complainer" segment.

Disclaimer: To be clear, there are very real problems discussed on social media, and people who express heart-breaking loss and pain. The aim of this post is not to trivialize these serious issues and I hope the distinction we are making is apparent.  

 

How Do You Find "Complainers" On Social Media?

We categorize location-based social media content (geosocial data) based on text similarity to reveal how areas compare with one another for a given social topic. Our analysis is more sophisticated than just looking at hashtags and keywords. Rather, these categories are generated through machine learning techniques. In other words, we didn’t set out to find "Complainers," it just happens to be a common type of conversation people naturally engage in on social media. 

 

What is a "Complainer?"

Some of the 200+ topics our text analysis organized for this specific category are:

underdressed, saddened, privileged, insignificant, ironically, ug (as in "ug, I have to go to class now.")

This group loves to share their problems with the world. They dramatize issues that an observer would often consider trivial.

 

Over-Indexing Areas for "Complainers" in Detroit

These are the areas that over-indexed (represented in green) for "Complainers" compared to the national average (national average = 0, 99th percentile = 10).  

Screen Shot 2018-08-13 at 10.18.14 AM


  • West Detroit
  • Southfield
  • Lathrup Village
  • Warren
  • Grosse Pointe

 

Implications

What would knowing this information help us with? Here are just a few scenarios in which this data could be applied:

Public Relations: It is not uncommon for unhappy customers to call out a company on social media, especially after failing to get a response from them. In fact, 46% of customers have used social to "call out" a brand. If "Complainers" are more likely to call out brands about what they've done wrong, knowing where they are could aid in preventing PR catastrophes. 

Mental Health Organizations: While the topics of conversation in regards to this segment are more trivial in nature, it may help measure the mental health of a community. Mental illness is on the rise for many reasons (increased social media engagement being one of them). Knowing which areas are more prone to mental illness could help health organizations provide appropriate care faster. 

 

The level of "Complainer" behavior can tell us a lot about an area, especially when observed alongside other social segments. What companies or use cases could you see this map being valuable for?

 

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