Eco-Amazon: Enriching E-commerce Datasets with Product Carbon Footprint for Sustainable Recommendations

This repository contains the Amazon datasets enriched with Product Carbon Footprint (PCF). Such dataset have been obtained by prompting state-of-the-art Large Language Models (LLMs) for estimating the PCF of Amazon products, in the Clothing, Electronics, Home & Kitchen domains. In particular, we exploit Google Gemini 2.5 Flash and OpenAI o3-mini to infer CO2e emissions based on product metadata, following strictly defined Life Cycle Assessment (LCA) standards (GHG Protocol, ISO 14040/14044). More details about the way these datasets have been enriched can be found in the associated paper and our repository for the source code. Metric Electronics Home & Kitchen Clothing Total Users 21,751 66,810 97,608 Total Items 11,495 17,027 21,380 Total Ratings 464,464 684,651 1,070,586 We provide these datasets in two forms: item metadata enriched with PCF estimations, one per LLM, in json format. For example, these are the Clothing datasets enriched with PCF estimations provided by Gemini-2.5-flash and GPT-o3-mini: clothing_gemini.jsonlclothing_o3mini.jsonl datasets in the RecBole format, used in our use case, whose code can be found in our GitHub Repository. As an example, the Amazon Clothing dataset in the RecBole format is the following: amazon_clothing.zip