What is Sentiment Analysis and How Does it Work?

[fa icon="calendar'] Apr 5, 2019 12:52:06 PM / by Bitext posted in API, Machine Learning, NLP, Sentiment Analysis, Big Data, Bitext, Natural Language, Text Analytics, Text Categorization, Chatbots, NLU, NLP for CX

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Sentiment Analysis is a procedure used to determine if a chunk of text is positive, negative or neutral. In text analytics, natural language processing (NLP) and machine learning (ML) techniques are combined to assign sentiment scores to the topics, categories or entities within a phrase.

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Are booleans the best option to analyze text?

[fa icon="calendar'] Oct 6, 2016 10:58:30 AM / by Tita Risueño posted in Text Categorization

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Last week we introduced you a controversial topic: how to achieve higher accuracy while doing text categorization? We explained the two most popular approaches to approach this challenge, namely keyword matching and linguistics.

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Text categorization beyond keyword matching

[fa icon="calendar'] Sep 29, 2016 12:50:26 PM / by Tita Risueño posted in Text Categorization

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There are different approaches for text categorization, the most popular one is based on keyword matching however here at Bitext we use another approach that has made us unique, and it’s based on linguistics.

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Are you happy with your call center? We are here to help!

[fa icon="calendar'] Sep 1, 2016 3:42:53 PM / by Tita Risueño posted in Text Categorization

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Text analysis technology has many applications outside from just feedback analysis. Call centers may seem out of date in this period where digital and email marketing are all around. However, in some industries like telecommunications or home utilities where many customers need to contact their service providers call centers can make order out of chaos. 

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Why Can’t your Hotel Live without Reputation Management?

[fa icon="calendar'] Aug 10, 2016 5:21:20 PM / by Bitext posted in Sentiment Analysis, Text Categorization, NLP for CX

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 Every business has only one reputation, and in a highly competititve market like the hospitality one, there is just one chance to give a good impression to your clients.

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