Scraping Tweets and Performing Sentiment Analysis

Sentiment Analysis is a special case of text classification where users’ opinions or sentiments regarding a product are classified into predefined categories such as positive, negative, neutral etc.  Public sentiments can then be used for corporate decision making regarding a product which is being liked or disliked by the public.

Both rule-based and statistical techniques have been developed for sentimental analysis.  With the advancements in Machine Learning and natural language processing techniques, Sentiment Analysis techniques have improved a lot.

In this tutorial, you will see how Sentiment Analysis can be performed on live Twitter data. The tutorial is divided into two major sections: Scraping Tweets from Twitter and Performing Sentiment Analysis.

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Postman REST API Client: Getting Started

REST technology is generally preferred to the more robust Simple Object Access Protocol (SOAP) technology because REST leverages less bandwidth, making it more suitable for internet usage.

REST APIs are all around us these days. Almost every major service provider on the internet  provides some kind of REST API. There are so many REST clients available that can be used to interact with these APIs and test requests before writing your code. Postman, is one of the world’s leading API Development Environment (ADE) with so many features baked in.

In this tutorial, you are going to learn how to use Postman to make API calls with and without authorization.

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Extracting YouTube Comments with YouTube API & Python

YouTube is the world’s largest video-sharing site with about 1.9 billion monthly active users. People use it to share info, teach, entertain, advertise and much more.

So YouTube has so much data that one can utilize to carry out research and analysis. For example, extracting YouTube video comments can be useful to run Sentiment Analysis and other Natural Language Processing tasks. YouTube API enables you to search for videos matching specific search criteria.

In this tutorial, you will learn how to extract comments from YouTube videos and store them in a CSV file using Python. It will cover setting up a project on Google console, enabling the necessary YouTube API and finally writing the script that interacts with the YouTube API.

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Yelp Fusion API tutorial

Yelp Fusion API is a REST API that gives access to information across 50 million businesses across countries.

In this tutorial, you will be learning how to use the Yelp API to search businesses by providing their names, locations or phone numbers. You will also learn to match businesses in a given location to check their availability. You will be using the requests library of Python, Requests and JSON library to parse the JSON response of data.

This tutorial covers the following features of the Yelp API: Business Search, Reviews Search, Phone Search, and Business Match.

Finally, there will be a practical project to help you use Yelp API in a real-life case.

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