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Twitter API with Python 2026 - using Tweepy | NLP Project Series - Part 1/3 | Sentiment Analysis

#Social Media Marketing
2025-12-24 21:579 min read

Content Introduction
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This video tutorial introduces data scientists to the process of configuring a Twitter developer account for data scraping, specifically focusing on utilizing Twitter's API for Natural Language Processing (NLP) projects. It highlights the significance of having an NLP project in a data science portfolio, discusses how to leverage Twitter as a valuable resource for text data, and explains the use of the Python library 'tweepy' for sentiment analysis of live tweets. The presenter demonstrates how to set up a developer account, acquire necessary credentials, and explains essential steps for generating access tokens and configuring read/write permissions for effective Twitter data retrieval. The tutorial sets the stage for further exploration and practical implementation of NLP tasks involving Twitter data, while encouraging viewers to subscribe for future project tutorials.

Key Information

  • The tutorial introduces the process of setting up a Twitter Developer account and using it for data science projects, particularly in Natural Language Processing (NLP).
  • Having a Twitter account is a prerequisite for creating a Developer account.
  • The tutorial guides users through configuring their Developer account to pull tweets using the Twitter API, particularly focusing on sentiment analysis.
  • Users will learn to use programming libraries like Tweepy to access Twitter's API and perform tasks such as sentiment analysis on tweets.
  • There is a focus on acquiring elevated access to pull a higher number of tweets and perform read/write operations, like posting or deleting tweets.
  • Throughout the tutorial series, users will be shown how to navigate the Twitter Developer Dashboard, including adding necessary permissions for their app.

Timeline Analysis

Content Keywords

Data Scientist

Introduction to a tutorial on natural language processing (NLP) projects for data scientists. Emphasizes the importance of having an NLP project in your portfolio to stand out.

Twitter API

Discussion about Twitter being a great resource for obtaining text data via its API, which provides easy access credentials and several libraries like Tweepy for integration.

Sentiment Analysis

Overview of a three-part series focusing on performing sentiment analysis on live tweets pulled from Twitter, including gauging public reactions.

Tweepy

Tweepy is introduced as a Python library to interface with the Twitter API. The tutorial will teach how to configure a Twitter developer account to pull tweets.

Developer Account

Instructions for creating a Twitter developer account, configuring it to access and pull tweets, including how to set up necessary credentials.

Elevated Access

Tutorial highlights applying for elevated access in the Twitter Developer Dashboard to increase the quota for pulled tweets, along with detailed steps for the application process.

Python Library

Using Python for accessing the Twitter API, including code snippets for installing libraries like Tweepy to interact with Twitter data efficiently.

Testing API

A practical test to pull tweets from Twitter based on a specific hashtag, demonstrating the functionality of the configured API and library in a Jupyter notebook.

Machine Learning Projects

Encouragement to subscribe for weekly updates on new machine learning projects, focusing on the use of Python and data science concepts in tutorials.

Related questions&answers

What is the purpose of setting up a Twitter developer account?

A Twitter developer account allows you to access Twitter's API, enabling you to interact with live tweets and perform tasks such as sentiment analysis.

How can I get started with a natural language processing project?

You can start by acquiring quality datasets, and consider using platforms like Twitter which have APIs to extract text data for your NLP projects.

Why is using Twitter's API beneficial for data science projects?

Twitter's API is a great resource for obtaining real-time text data, and it provides easy-to-use libraries, such as Tweepy in Python, for efficient data handling.

What is Tweepy?

Tweepy is a Python library that allows you to interact with Twitter's API, enabling you to tweet, read timelines, and obtain user information programmatically.

What do I need to set up before I can access Twitter's API?

You need to create a Twitter account, sign up for a developer account, and generate API keys and access tokens.

How do I configure my Twitter developer account?

To configure your account, log in to the Twitter Developer Portal, complete necessary information and agree to the terms of service, and then generate your API keys.

What kind of access do I need to perform actions like tweeting or deleting tweets?

You need both read and write access, which can be set up in the user authentication settings of your Twitter developer account.

Why shouldn't I share my API keys and tokens?

API keys and tokens are sensitive credentials that provide access to your account, and sharing them can lead to unauthorized access or misuse of your Twitter data.

What should I do if I encounter issues while setting up my developer account?

You can post your concerns in the comments section of the tutorial, and assistance will be provided to help resolve your issues.

How frequently are new machine learning projects posted?

New machine learning projects are posted every week on the channel.

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