The Mismatch: Why lower ratings? We used a fine-tuned BERT model to analyze review text. The results suggest an increase in consumer-book mismatches.

With reduced diversity (a shrinking "long tail"), readers were more likely to receive books misaligned with their preferences.

The Demand Paradox: How did readers (demand side) respond? The promotional effects intensified, but with a paradox.

Books in the paid program received a HIGHER volume of reviews, but LOWER average ratings. Monetization amplified the "Groupon effect."

The "Rich-Get-Richer" Dynamic: Diving deeper, we saw a "rich-get-richer" effect. Popular genres (like Mystery/Thriller) became more dominant, while niche genres (like Poetry/Science) lost market share. The entry cost narrowed the range of cultural products being promoted.

The Diversity Drop: This shift in suppliers directly affected product variety. We measured a significant decline in the diversity of book genres available in the program post-monetization. The marketplace became less varied.

Market Concentration & Author Profiles: This led to a massive 200% increase in market concentration (HHI). Furthermore, the authors who continued to participate post-monetization were generally more established, popular, and experienced with the platform.

Uneven Impact & Concentration: Importantly, the impact was uneven. The cost disproportionately pushed out indie publishers and self-published authors.

While overall participation dropped, the market share of the "Big 5" publishing houses more than doubled (12% to 30%).

The Supply Shock: The impact on the supply side was immediate and dramatic. Introducing the entry cost caused the average number of monthly promotional campaigns to plummet from ~3,000 to ~1,000.

We studied the Goodreads "Giveaways" program, a marketplace for book promotion. It was free for authors/publishers until Jan 2018, when Goodreads introduced a fixed $119 entry cost.

This provided a natural experiment to study monetization in a two-sided market.

📣 Thrilled to announce our new paper, "Monetizing Platforms: An Empirical Analysis of Supply and Demand Responses to Entry Costs in Two-Sided Markets," is now published in Management Science!

When a digital platform starts charging for access, who wins and who loses? 🧵👇

Our analysis of content reveals mixed progress: biographical and geographical content are moving toward better representation, yet disparities persist.

However, the benefits aren’t equally distributed. Languages with larger content bases and active communities see much larger gains in content creation compared to smaller editions.

Reader engagement remains robust too. Translated articles show consistent pageviews, and combined source–target readership increases overall reach.

On the quality front, despite the surge in translation volume, we observe lower deletion rates and a modest improvement in structural quality scores.

Our findings are striking: content translation volume increased by 149% on average—demonstrating how AI lowers language barriers and significantly increase cross-language knowledge transfer.

We leverage Wikipedia’s integration of Google Translate (Jan 2019) as a natural experiment. This integration provides editors with a more advanced technology (transformer-based MT) for translating content across languages.

Excited to share our revised working paper on Machine-assisted Content Creation on Peer Production Platforms—we have made significant changes and additions!

Our study explores how AI-powered translation reshapes multilingual content creation on platforms like Wikipedia.

I should be working on my paper revision, but I could not stop myself from pulling relevant data and creating this plot:

Elon Musk's Wokepedia attack seems to act as a surprisingly effective call for donations!