Insights from 140 Characters: #Twitter #SentimentAnalysis

[fa icon="calendar'] Aug 18, 2016 12:49:59 PM / by Tita Risueño posted in API, NLP, Sentiment Analysis, NLP for CX

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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
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Case Study: Customer insights in minutes

[fa icon="calendar'] Jul 6, 2016 10:10:34 PM / by Bitext posted in API, Bitext

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Time flies for everyone — particularly while working. We always have the sensation of having much to do and not enough time to do it all. That is why it’s necessary to include in our daily routine tools that allow us to save time. Preparing large amounts of datasets and analyzing them to extract insights is one of those time consuming tasks.

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Uncover Business Critical Insights with Topic-based Sentiment Analysis

[fa icon="calendar'] Jun 30, 2016 8:12:23 AM / by Bitext posted in API, Sentiment Analysis, NLP for CX

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Last week’s post explored the differences between polarity and topic-based sentiment analysis (have a look here if you missed it). This post goes a step further, drilling down into a real data set to demonstrate the true value of topic-based sentiment analysis.

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Differences between Polarity and Topic-Based Sentiment Analysis

[fa icon="calendar'] Jun 16, 2016 8:25:48 PM / by Bitext posted in API, NLP, NLP for CX

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From a business perspective, there is huge difference between plain polarity and topic-based sentiment analysis (also known as aspect-based sentiment analysis)

 
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What's the Use of Sentiment Analysis at the Document Level? Not Much, without Topic-Level Analysis

[fa icon="calendar'] Aug 5, 2014 1:00:00 AM / by Bitext posted in API, Sentiment Analysis, NLP for CX

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Quite often, documents express opinions, like web reviews or open-ended questions in market surveys. And most of the times documents don’t just represent a single point of view, a single opinion. Documents typically consist of multiple opinions representing several closely related but nuanced positions. By reducing a whole document to a single opinion score, many sentiment analysis services hide the best insights, the useful ones, and prevent clients from drilling down to extract the useful information.

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