Analyzing Vegan Trends on Twitter
Contents
- /Notebooks
Three separate notebooks describing the process of collecting tweets, processing the tweets, and visualizing the resulting model - /Data
All of the .txt files contain the tweets used in this project - /Py_Files
Python files containing functions and classes used throughout the project and notebooks - /Images
Important images used in the analysis and presentation - Presentation Slide Deck
Extras: Read the blog post.
Description
This project uses NLP to explore the conversation about veganism on Twitter. Over 60,000 tweets were collected and grouped into topics to determine trends in the vegan world. Everything I used is included in this repository for further exploration and insight.
Topics
- Food Topics
Salads, Desserts, Breakfast, Meals, 'Fake' Foods, Ice Cream, Baking, Cheese, Vegetables + Ingredients - Lifestyle Topics
Fitness + Weightloss, Nutrition, Lifestyle, Restricted Diets, Dating, Positivity - Media Topics
Blogs + Articles, Social Media, Vegan Hastags, Contests - Bath Topics
Beauty Products, Skin Care, Soap - Animal Topcis
Animal Activism
Tools Used
- Natural Language Processing
- snscrape
- Topic Modeling
- NLTK
- LDA
- NMF
- Seaborn
- Matplotlib
- Numpy
- Pandas
- JSON
Potential Impact & Use
This repository is good for those looking into scraping Twitter and then turning that scraped data into insights. In regards to the insights pulled from this exploration, trends are moving towards animal activism and 'fake' foods. Companies can take note that 'fake' foods are hot and worth looking into for investment and even 'fake' food companies can know that their marketing efforts are working.
