Viewing entries tagged
sentiment analysis

TUTORIAL: SCRAPING AND ANALYSING AMAZON REVIEWS

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TUTORIAL: SCRAPING AND ANALYSING AMAZON REVIEWS

In this tutorial we will show you how to scrape reviews from an amazon product page. This data can be used to create datasets for sentiment analysis or other educational or research purposes. If you sell products on Amazon it can even be useful to analyse the reviews to understand what customers like and dislike about your product. Let's dive in!

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Tutorial: Find Semantic Similarities Across Facebook Posts

Tutorial: Find Semantic Similarities Across Facebook Posts

In this tutorial we will use modern Natural Language Processing techniques to find similar posts in a Facebook group. You have probably been in a situation where you want to post something in a Facebook group but you are not sure whether almost the same post already exists and is maybe just hiding on the next page. This technique will prevent you from bothering the group users with repeating questions :-)

Tutorial: Create Your Own API - Part 3

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Tutorial: Create Your Own API - Part 3

This is the third installment of a short series on how to build our own API. In the last two weeks, we have shown you how to create your own Flask application and how to build a sentiment classifier from tweets using the Twitter API and nltk. Today we will combine these two things to make them work together. Get comfortable, let's dig in! 

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Tutorial: Create Your Own API - Part 2

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Tutorial: Create Your Own API - Part 2

Last week we introduced you to the very basics of Flask framework and now we will show you how to create your own model for sentiment analysis. To build our dataset for training, we will use the well-known Twitter API.

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