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A Researcher’s Guide to RentHub: Rental Listings Data for Academic Use

May 8, 2025
By
Dewey Data

Explore how RentHub’s granular, standardized rental listing data empowers academic research in housing, urban development, and affordability.

Why Rental Data Matters for Academic Researchers

Academic researchers exploring housing markets, urban development, or affordability trends often struggle to find rental data that is both comprehensive and usable. Many datasets are either too limited in scope, outdated, or inconsistently structured.

RentHub, in partnership with Dewey Data, solves this by offering a standardized, nationwide dataset built from over 1 million rental listings collected weekly across 41,000+ U.S. ZIP codes. This dataset gives scholars a powerful foundation for rigorous, data-driven research.

What Makes RentHub Different from Other Rental Data Providers?

While there are other sources of rental data on the market, RentHub stands out due to:

Data Consistency Through Natural Language Processing

RentHub applies advanced NLP techniques to extract and standardize property features from unstructured listings. This makes cross-market comparisons possible and accurate.

Unmatched Geographic Coverage

Covering virtually every ZIP code in the United States, RentHub gives you access to rental dynamics in both major metros and rural communities—something most providers don’t offer.

Property-Level Granularity

Rather than relying on aggregated indices, RentHub provides raw, listing-level data including attributes such as rent price, square footage, number of bedrooms, and amenities.

Rich Metadata and Unit Descriptions

In addition to structured attributes, RentHub captures full marketing descriptions, allowing researchers to perform text analysis on rental marketing language.

Weekly Updates

With fresh data collected every 7 days, RentHub ensures your research reflects current trends rather than stale quarterly summaries.

These differentiators make RentHub particularly attractive for academic projects that demand high-resolution, frequently updated, and deeply contextualized rental data.

A Deep Dive Into RentHub’s Rental Dataset

RentHub's dataset encompasses a wide array of property types, including single-family homes, apartments, and condominiums. Each listing is enriched with detailed attributes such as:

  • Rental price

  • Number of bedrooms and bathrooms

  • Square footage

  • Property type and amenities

  • Latitude/longitude

  • Full-text marketing descriptions

The result is a highly structured, research-ready dataset that can be directly applied to urban studies, housing economics, sociology, public policy, and beyond. To see all available attributes, visit the RentHub documentation page.

Real-World Research Applications

The richness of RentHub’s data supports a wide range of academic research themes:

Housing Affordability and Displacement

Track changes in rent levels over time to analyze affordability by neighborhood or income bracket.

Urban Development and Infrastructure Impact

Study the influence of new public infrastructure (e.g., transit lines, parks) on local rental markets.

Sociological Research

Investigate correlations between rental market characteristics and demographic or socioeconomic factors.

Policy Evaluation and Planning

Evaluate the effects of rent control laws, zoning changes, or eviction moratoriums on market trends.

Interested in other Real Estate datasets? Check out our post on Real Estate data for academic research. 

Easy Access Through Dewey Data’s Platform

Dewey Data streamlines the process of accessing RentHub's comprehensive dataset for academic purposes

  • Flexible Licensing: Tailored subscription models accommodating individual or institutional needs.

  • Integrated Data Ecosystem: Combine RentHub data with other datasets available on Dewey for enriched analyses.

  • Dedicated Support: Access to a team of data experts to assist with data integration and research design

To get started simply log on to app.deweydata.io with your university email and search RentHub to preview and sample the datasets. For additional resources check out RentHub Documentation.