https://github.com/nicolasgasco/python_twitter_analyzer
Capstone project of CodingNomads' online Python Programming bootcamp. Over 100k tweets were mined using tweepy (Twitter API), stored using SQLAlchemy and finally analyzed.
https://github.com/nicolasgasco/python_twitter_analyzer
python sql sqlalchemy sqlalchemy-database sqlalchemy-python tweepy tweepy-api tweet-analysis twitter twitter-api
Last synced: 4 months ago
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Capstone project of CodingNomads' online Python Programming bootcamp. Over 100k tweets were mined using tweepy (Twitter API), stored using SQLAlchemy and finally analyzed.
- Host: GitHub
- URL: https://github.com/nicolasgasco/python_twitter_analyzer
- Owner: nicolasgasco
- Created: 2020-12-03T18:29:58.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-05-16T13:48:02.000Z (about 4 years ago)
- Last Synced: 2025-01-15T01:44:27.613Z (6 months ago)
- Topics: python, sql, sqlalchemy, sqlalchemy-database, sqlalchemy-python, tweepy, tweepy-api, tweet-analysis, twitter, twitter-api
- Language: Python
- Homepage:
- Size: 9.11 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# Python Twitter Analyzer
## [CodingNomads](https://codingnomads.co/) final project using tweepy and sqlalchemy
---
This is the final project of the online [Python course](https://codingnomads.co/courses/python-bootcamp-online/) by CodingNomads.
### Aim
The aim of the project is providing a series of statistics (e.g. average user count or most popular hours) on a set of Twitter tweets fetched using *tweepy* and stored in a database using *sqlalchemy*.
The results of said statistics can be previewed in the three .txt files in the main folder of the project:
- results_text_analysis.txt: stats on the text of the tweets, e.g. most frequently used symbols and longest word in the set.
- results_time_analysis.txt: stats on the time when the tweets were written, e.g. most popular hours or oldest tweet.
- results_users_analysis.txt: stats on the users, e.g. users with most followers or average followers/followed accounts ratio.
### Description
The project consists of a series of scripts aimed at:
1. Use *tweepy* to fetch a list of users who recently wrote a tweet in English containing the word "cyberpunk". This was done to push the set of tweets towards the gaming world.
2. Use *tweepy* to fetch the last 20 tweets published by said users. Only tweets in English and that are not retweets of other tweets were accepted.
3. Use *sqlalchemy* to store and retrieve all the data in a database.
4. Use python scripts to analyze the collected data (one file where the results are printed and written in a .txt file and another with all the actual functions used).
5. All data was stored in the database provided in the homonymous separate folder.