Abstract: You will enjoy this talk if you’re interested in:
• Making the world more transparent
• Making Retail more sustainable
• Learning more about scraping and NLP
Our resources are finite. Fortunately, many retail organisations are aware of this and lead the transition towards increased sustainability. Moreover, the modern fast-fashion industry is still dominated by the pressure to produce fast and cheap. Every time you buy a piece of clothing, you therefore have a choice to make, a choice that impacts our planet and the people producing your clothing.
Great initiatives are underway to help you make this choice and push producers into the right direction. Unfortunately, complete and reliable information is lacking. Therefore, we started an open-source NLP project to predict the sustainability of a clothing brand based on information from their website. By using companies’ own websites, we can provide accurate and timely information. Moreover, our model is self-learning and dynamic: it will adjust the explainable sustainability criteria as brands provide more and better information.
Using this method, we are able to rate thousands of (clothing) brands and provide a database which contains more brands than you can think of, which is updated as often as desired and adapts over time. Our open-source system (available via https://gitlab.com/thehup/duurzame-benchmark) provides well-founded and reliable estimates of the level of sustainability of each specific brand.
This talk will inform you about the general process and steps we have taken, as well as (technical) challenges and solutions, which should help you in setting up or improving your own open-source NLP project. Moreover, we will discuss possible improvements and encourage debate to further improve our project.
This year’s talk is aimed at raising awareness; if all goes well, we would like to organise a panel discussion at next year’s ODSC, to bring this topic even further.
Bio: Joanneke is a Manager at Amsterdam Data Collective and initiator of the sustainable benchmark. She is an experienced data-science consultant, focusing on forecasting, pricing, operational research and text mining. By coaching teams towards delivering actionable insights from data, she continuously manages to create sustainable impact.
Data Science Manager | Amsterdam Data Collective