Analyzing customer support interactions on Twitter with Machine Learning

We are seeing new trends in customer support. Some companies are starting to have a different social media appearance, trying to appear more hip and cool (probably actual words used by executives). Instead of making their social media managers behave in a professional servile-like fashion, these companies opt instead to communicate in a more personal way.

Some signs of this approach are every member of the social media team signing with their name, and engaging in conversations with users that don’t involve the company at all (but usually involving memes). These conversations can even involve friendly banter, which was absolutely unthinkable in the old days. This way of doing customer support gained a lot of attention with the viralization of Wendy’s Twitter account earlier this year.

Other companies are apparently following suit, spicing up their social media channels with personality. The question we aim to explore here is, does this actually work? We compare Twitter sentiment of different telcos to find out. Some carriers approach Twitter in a traditional way, while others try to be more loose.

Which one elicits the most positive tweets? The most negative tweets? Which one is more liked? What are these users saying? Let’s find out!

In order to perform sentiment analysis, we used MonkeyLearn’s public Twitter sentiment analysis module, which will classify tweets with positive, neutral or negative labels. We downloaded tweets mentioning one of the four big carriers (Verizon, T-Mobile, AT&T, Sprint) using tweepy, and classified them with the MonkeyLearn python client. What this gives us is a lot of tweets, each one mentioning one telco and with a sentiment label.

Now, let’s see what we can learn from this.

On a given week, the average number of tweets mentioning a company (either by name or by handle) has AT&T on top, with an average of 64,000 tweets a week.

This was pretty surprising on its own, especially considering that Verizon and AT&T have almost the same number of subscribers. Also, Verizon has a lot more followers than AT&T, yet they have half the number of tweets on any week. This by itself is interesting, since one would expect carriers with a similar number of subscribers (or Twitter followers) to have the same number of mentions.

Now, raw numbers are cool, but we want to know the sentiment of the users that posted these tweets and that interacted with the telcos customer support on Twitter. Are they happy customers, or angry detractors? Are they glad or indifferent towards their carrier? Are they complaining about a particular issue? To find out, we calculated the percentage of tweets of each sentiment — positive, neutral or negative — in the total of tweets for each company.

On the positive side, clearly on top comes out T-Mobile, with 20% of the tweets mentioning them being positive. They are ahead by their next competitor, Sprint, by a 5 percent points and have double the rating than the larger companies, AT&T and Verizon. Interestingly, the larger companies have less positive tweets than the smaller ones.

Now on the neutral side, turns out most tweets are actually neutral tweets: these are mostly factual questions, answers, or opinions that don’t express a sentiment. Here, the largest carriers have the bigger chunk of their tweets with neutral sentiment. So far what we are seeing is that a larger percentage of people are simply talking about them, without expressing a sentiment. This means either customer support, or news mentioning them.

Now when it comes to negative tweets, we were surprised: in proportion most companies receive less negative tweets than positive ones. This was honestly pretty unexpected, considering Twitter’s constant flamewars. The only exception is Verizon: they are the only ones that have more negative tweets than positive ones. This would mean that as far as Twitter sentiment goes, Verizon is seen as the worst carrier of all.