Insights from 140 Characters: #Twitter #SentimentAnalysis

Searches about "sentiment analysis" are increasing, particularly related to Twitter. However not all the tools available in the market can face the problem analyzing 140 characters. In this post we will show you:

 

  • Real comments analized
  • See how text is structured
  • Short texts are not an issue

According to Statista there are 313 million people using Twitter actively, that is more or less 23% of the total adults in the world. So it is not really a leap of faith to think that a large portion of your customers will be using it.


Most of the companies have accepted this social platform as a channel to communicate with clients. In fact, some of them have created independent accounts focused on customer service. All to be more effective at listening to their customers and react in an agile way to suggestions or complains.


However, listening is not enough for a business. Communication with clients is not enough if the feedback received goes nowhere or if you are not able to objectively measure how things are going. The challenging part is what comes next: analyze the messages you have received to enhance your business performance.


That is the step that differentiate customer centric companies from the rest, and as we said in a previous post, that directly translate in to profits.


Collecting tweets, it’s not a real challenge. You can do so either through the Twitter API or third party offerings. The hard -and boring- work comes later, when you need to read an analyze the content. This process can be done manually but it requires time, effort and what is worse you will probably end up with biased results that are not comparable over time. Using sentiment analysis provides you accurate, consistent and impartial results.

But…how does it work? How do I know it’s the right tool for me?


While writing in Twitter you just have 140 characters so we try to express as many opinions as possible in one sentence. And we don’t use our best grammar and punctuation signs to do so. You need a robust Text Analysis platform to be able to extract useful info from those short sentences.


Our aspect based sentiment analysis not only shows you polarity and intensity of sentiment. But also shows what is being spoken about in those twitter comments. You can use the sentiment end point of our API to continuously analyze the twitter comments that relevant to your business and deliver them exactly where you want.

And to get a feeling of what the end results will be click in our downloadable and get a sample of freshly analyzed tweets written by the customers of a well-known airline.

Download a Real Case

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