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Twitter API with Python 2022 - using Tweepy | NLP Project Series - Part 1/3 | Sentiment Analysis

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In this tutorial, we shall discuss how to configure a Twitter Developer Account (with API v2) that allows you to pull 2 million tweets per month.
In this three part learning series, we are going to perform Sentiment Analysis on live tweets duly pulled from twitter, and use it to tell whether people are happy about the new iPhone announcement, or Americans are still missing their beloved president Donald Trump :-)
🔥 Links to the entire series:
This is the first part to this three part series.
In the upcoming parts, I will introduce you to a Python library called Tweepy, that enables Python to communicate with Twitter platform and consume its API. And lastly, we shall perform sentiment analysis and visualizations on live tweets, pulled from twitter.
Having a Natural Language Processing or NLP Project in your Data Science Portfolio makes your CV stand-out. But, getting hold of a quality dataset might come in your way. Well, not anymore. Twitter is, actually, a great resource for getting text data, as:
- it has an API,
- credentials are easy to acquire and
- there are a number of python libraries available to consume Twitter’s API, like: Tweepy
Happy learning :)
🔥 Sections
00:00 Introduction
01:17 Prerequisites
02:58 Twitter Developer Portal
04:12 Elevated Access for 2M tweets
05:51 Read & Write Access
06:59 Final API Keys
07:47 Testing API Integration
08:23 Up next: Tweepy Intro
🔥 Resources:
Our other popular ML Projects:
2. Sentiment Analysis Project (End-to-end) with ML Model Building + Deployment (using Flask):
🔥 Do like, share & subscribe to our channel. Keep in touch:
Whatsapp: +91-7404139793
In this three part learning series, we are going to perform Sentiment Analysis on live tweets duly pulled from twitter, and use it to tell whether people are happy about the new iPhone announcement, or Americans are still missing their beloved president Donald Trump :-)
🔥 Links to the entire series:
This is the first part to this three part series.
In the upcoming parts, I will introduce you to a Python library called Tweepy, that enables Python to communicate with Twitter platform and consume its API. And lastly, we shall perform sentiment analysis and visualizations on live tweets, pulled from twitter.
Having a Natural Language Processing or NLP Project in your Data Science Portfolio makes your CV stand-out. But, getting hold of a quality dataset might come in your way. Well, not anymore. Twitter is, actually, a great resource for getting text data, as:
- it has an API,
- credentials are easy to acquire and
- there are a number of python libraries available to consume Twitter’s API, like: Tweepy
Happy learning :)
🔥 Sections
00:00 Introduction
01:17 Prerequisites
02:58 Twitter Developer Portal
04:12 Elevated Access for 2M tweets
05:51 Read & Write Access
06:59 Final API Keys
07:47 Testing API Integration
08:23 Up next: Tweepy Intro
🔥 Resources:
Our other popular ML Projects:
2. Sentiment Analysis Project (End-to-end) with ML Model Building + Deployment (using Flask):
🔥 Do like, share & subscribe to our channel. Keep in touch:
Whatsapp: +91-7404139793
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