Problem

Many fashion companies draw attempts to establish ethical reputations by releasing statements on issues such as environmentalism. Despite the strong language, however, consumers are often skeptical of the messaging. Websites, such as Good on You, attempt to educate consumers of company practices; often identifying “greenwashing” statements through their platform. But educating oneself is a time-consuming process, so how could consumers become more aware of these so-called “green-washed” statements?

Adopting similar methods for building spam detection models, we approached this problem from a data science perspective.

In this project, we will explore the following questions:

• What aspects of online brand statements predict company ethical ratings, specifically in the athleisure industry?
• What is the impact of sustainability practices of a brand for customer fashion purchases?

Proposal

With these questions in mind, our proposed solutions include:

• Building a classification model to identify ethical and unethical companies based on language used in company statements
• Assessing consumer perceptions on topics of company ethics and sustainability practices based on fashion subreddit posts and comments

Datasets

• Company Data: Athleisure brand statements on sustainability from owned website
• Good on You: Brand Directory with thousands of brands and associated ethics rating
• Social Media Following in Twitter, Instagram, and Facebook
• Text data scraped from the subreddits femalefashionadvice and malefashionadvice on Reddit.com

Table of contents

1. documents includes project-related PDFs and images
2. scrapers: includes all scripts for scraping data from reddit
3. preprocessing: includes all preprocesing scripts for NLP analyses
4. analyses: exploratory analysis scripts using NLP (to be added soon)