In recent years, two-sided marketplaces have emerged as viable business models in many real-world applications. In particular, we have moved from the social network paradigm to a network with two distinct types of participants representing the supply and demand of a specific good. Examples of industries include but are not limited to accommodation (Airbnb, Booking.com), video content (YouTube, Instagram, TikTok), ridesharing (Uber, Lyft), online shops (Etsy, Ebay, Facebook Marketplace), music (Spotify, Amazon), app stores (Apple App Store, Google App Store) or job sites (LinkedIn). The traditional research in most of these industries focused on satisfying the demand. OTAs would sell hotel accommodation, TV networks would broadcast their own content, or taxi companies would own their own vehicle fleet. In modern examples like Airbnb, YouTube, Instagram, or Uber, the platforms operate by outsourcing the service they provide to their users, whether they are hosts, content creators or drivers, and have to develop their models considering their needs and goals.

The two-sided marketplaces are almost entirely data-driven. Machine learning powered methods and algorithms are essential in every aspect of two-sided marketplaces. This workshop aims to bring practitioners of two-sided marketplaces together and discuss the evolution of content ranking, recommendation systems, and data mining when solving for producers and consumers on these platforms. Additionally, the workshop will cover Generative AI applications in these platforms and how they are changing the ecosystem.

The topics of this workshop include, but are not limited to, the following:
- Search in two-sided marketplaces
- Recommendation Systems in two-sided marketplaces
- Generative AI applications in two-sided marketplaces
- Online matching and rebalancing in two-sided marketplaces
- Embedding applications in two-sided marketplaces
- Retrieval-augmented generation (RAG) applications in two-sided marketplaces
- Growth and Monetization for two-sided marketplaces
- Marketing Strategies
- Dynamic Pricing and Price Recommendations
- Fraud and fake-content Detection
- Privacy
- Battle scars and lessons learned from deploying real-world systems


Format

Papers must be submitted in PDF in ACM Conference Proceeding template (two column format). Submissions should not exceed 8 pages plus up to one additional page of references.

Microsoft Word template guideline: https://www.acm.org/publications/proceedings-template

LaTeX template guideline: https://www.overleaf.com/latex/templates/association-for-computing-machinery-acm-sig-proceedings-template/bmvfhcdnxfty

The recommended setting for Latex documents is: \documentclass[sigconf, review]{acmart}