New York City accounted for ****** Airbnb listings in late 2024. Meanwhile, Los Angeles had ****** listings, making it the city with the most Airbnb listings in the ranking.

As of December, 2024, there were over ** thousand listings for room and apartment rentals in London on the Airbnb website, the highest of any other major European city. Airbnb listings were also high in Paris, Rome and Madrid. Paris accounted for around ** thousand listings, while Rome and Madrid had over ** and ** thousand, respectively. Controversy of Airbnb in Europe Airbnb has become an increasingly popular option for tourists looking for local accommodation. Visitors are attracted to using Airbnb properties instead of hotels and other traditional travel accommodation mainly due to cheaper prices, but also for the location, and to gain an authentic experience. However, the site is facing ongoing legal problems, with some destinations moving to ban or restrict rentals from the site because they worsen housing problems and undermining hotel regulations. Many European cities, including Amsterdam and Paris, have placed limits on the length of rentals, and others such as Barcelona have introduced strict regulations for hosts. The rise of Airbnb Airbnb is one of the most successful companies in the global sharing economy. The company was founded in San Francisco, California in 2008, after being conceived by two entrepreneurs looking for a way to offset their high rental costs. Airbnb was developed as an online platform for hosts to rent out their properties on a short-term basis. It now competes with other online travel booking websites, including Booking.com and Expedia.

Data Set Information This data set describes the listing activity of Airbnb homestays in New Orleans, Louisiana, as part of the Inside Airbnb initiative. The data set was compiled on November 7, 2021. See the New Orleans Airbnb data visually here.

Some personally identifying information has been removed from the data uploaded here.

Contents The following Airbnb activity is included in this New Orleans data set:

Listings, including full descriptions and average review score (new_orleans_airbnb_listings.csv) Reviews, including unique id for each reviewer and detailed comments (reviews.csv)

Acknowledgements Data credit goes to Murray Cox and Inside Airbnb. The original source for this particular New Orleans data can be found here--where you can also find information on the different listing ids and their price and availability for different calendar dates (if you're interested in looking at how Airbnb rental listing price fluctuates over time).

Context The data set can be used to answer some interesting questions, such as:

Can you predict how much a short-term rental in New Orleans should charge per night based on it's location and amenities? Can you describe the vibe of each neighborhood in using listing descriptions? What are the most common amenities to have among short-term rental listings in New Orleans? What elements contribute to a popular or highly-rated listing? Is there any noticeable difference in favorability among different NOLA neighborhood/areas and what could be the reason for it? Furthermore, it's also important to note that Inside Airbnb (provider of dataset) is a mission driven activist project with the objective to provide data that quantifies the impact of short-term rentals on housing and residential communities; and also provides a platform to support advocacy for policies to protect cities from the impacts of short-term rentals.

According to travel guides, New Orleans is one of the top ten most-visited cities in the United States. It was severely affected by Hurricane Katrina in August 2005, which flooded more than 80% of the city, killed more than 1,800 people, and displaced thousands of residents, causing a population decline of over 50%. Since Katrina, major redevelopment efforts have led to a rebound in the city's population. Concerns about gentrification, new residents buying property in formerly closely knit communities, and displacement of longtime residents have all been a major discussion topic.

Bearing the given context in mind, this data set shared by Inside Airbnb also allows you to ask fundamental questions about Airbnb in any neighbourhood, or across the city as a whole, such as:

How many listings are in my neighbourhood and where are they? How many houses and apartments are being rented out frequently to tourists and not to long-term residents? How much are hosts making from renting to tourists (compare that to long-term rentals)? Which hosts are running a business with multiple listings and where they? The questions (and their answers) get to the core of the debate for many cities around the world, with Airbnb claiming that their hosts only occasionally rent the homes in which they live. In addition, many city or state legislation or ordinances that address residential housing, short term or vacation rentals, and zoning usually make reference to allowed use, including:

how many nights a dwelling is rented per year minimum nights stay whether the host is present how many rooms are being rented in a building the number of occupants allowed in a rental whether the listing is licensed

Original Data Source: New Orleans Airbnb Listings and Reviews

Listings per region on Airbnb declined from 2020 to 2021. Globally in 2021, there were a total of 12.7 million listings.

The current average price per night globally on Airbnb is $137 per night.

Inside Airbnb is an independent, non-commercial set of tools and data that allows you to explore how Airbnb is really being used in cities around the world.By analyzing publicly available information about a city's Airbnb's listings, Inside Airbnb provides filters and key metrics so you can see how Airbnb is being used to compete with the residential housing market.With Inside Airbnb, you can ask fundamental questions about Airbnb in any neighbourhood, or across the city as a whole. Questions such as: "How many listings are in my neighbourhood and where are they?""How many houses and apartments are being rented out frequently to tourists and not to long-term residents?""How much are hosts making from renting to tourists (compare that to long-term rentals)?""Which hosts are running a business with multiple listings and where they?"The tools are presented simply, and can also be used to answer more complicated questions, such as: "Show me all the highly available listings in Bedford-Stuyvesant in Brooklyn, New York City, which are for the 'entire home or apartment' that have a review in the last 6 months AND booked frequently AND where the host has other listings."These questions (and the answers) get to the core of the debate for many cities around the world, with Airbnb claiming that their hosts only occasionally rent the homes in which they live.In addition, many city or state legislation or ordinances that address residential housing, short term or vacation rentals, and zoning usually make reference to allowed use, including: how many nights a dwelling is rented per yearminimum nights staywhether the host is presenthow many rooms are being rented in a buildingthe number of occupants allowed in a rentalwhether the listing is licensedThe Inside Airbnb tool or data can be used to answer some of these questions.The data behind the Inside Airbnb site is sourced from publicly available information from the Airbnb site.The data has been analyzed, cleansed and aggregated where appropriate to faciliate public discussion. Read more disclaimers here.If you would like to do further analysis or produce alternate visualisations of the data, it is available below under a Creative Commons CC0 1.0 Universal (CC0 1.0) "Public Domain Dedication" license.

This is the complete breakdown of how much revenue Airbnb makes in commission from listings in each region.

The majority of guests on Airbnb are women. Most Airbnb guests are aged 25 to 34.

These are the Airbnb statistics on gross revenue by country.

Airbnb has a total of 6,132 employees that work for the company. 52.5% of Airbnb workers are male and 47.5% are female.

London continued to dominate the Airbnb market in the United Kingdom, with over 95,000 listings as of December 2024. This figure was by far the highest among other major UK cities, with Greater Manchester and Edinburgh trailing behind at 6,811 and 5,670 listings, respectively. The stark contrast highlighted London's position as a prime destination for short-term rentals and its appeal to both domestic and international travelers. Accommodation preferences across cities in Europe As of December 2024, the most common type of Airbnb listings in London were for entire homes or apartments, accounting for nearly two thirds of the total. Meanwhile hotel rooms represented a mere 0.2 percent of listings. This trend was mirrored in other European cities, with Berlin and Vienna also showing a preference for entire home listings. The most common types of Airbnb listings in Berlin, featured nearly two-thirds of the approximately 14,000 listings being for entire homes, while the most common types of listings in Vienna boasted almost 12,000 entire home listings out of a total of around 14,600. How do London’s Airbnb listings compare to other major European cities? In a broader context, London remained the leader in total Airbnb listings per city in Europe in 2024, boasting over 4,000 more listings than Paris, which came in second place. However, when considering listings per capita in Europe, Paris emerged as the frontrunner with approximately 45 listings per 1,000 inhabitants in 2024. This high density of short-term rentals led to increasing scrutiny and regulation across European cities.

According to a March 2025 analysis, Rome reported the highest number of Airbnb listings among the selected Italian cities. As of that month, there were over 34,000 establishments listed on Airbnb in the Italian capital. Milan and Florence followed behind, with over 16,000 and 12,000 listings on Airbnb. What are the leading brands for accommodation bookings in Italy? According to the Statista Consumer Insights Global survey, Airbnb was the second most popular brand for hotel and private accommodation online bookings in Italy in 2024, with over a quarter of respondents having booked accommodation via that website. That year, Booking.com topped the ranking, with almost three-quarters of the sample reporting using that provider. Booking Holdings vs. Airbnb Booking Holdings, which operates the Booking.com brand, and Airbnb are among the biggest companies in the online travel market. In 2025, Booking Holdings had the highest market cap of the leading online travel companies worldwide, while Airbnb ranked second. Both companies experienced an annual increase in earnings in 2024. That year, Booking Holdings' revenue peaked at almost 24 billion U.S. dollars. Meanwhile, Airbnb's revenue also reached an all-time high for the company in 2024.

Context

Since 2008, guests and hosts have used Airbnb to expand on traveling possibilities and present more unique, personalized way of experiencing the world. This dataset describes the listing activity and metrics in NYC, NY for 2019.

Content

This data file includes all needed information to find out more about hosts, geographical availability, necessary metrics to make predictions and draw conclusions.

Acknowledgements

This public dataset is part of Airbnb, and the original source can be found on this website.

Inspiration

• What can we learn about different hosts and areas?
• What can we learn from predictions? (ex: locations, prices, reviews, etc)
• Which hosts are the busiest and why?
• Is there any noticeable difference of traffic among different areas and what could be the reason for it?

In 2007, a cash-strapped Brian Chesky came up with a shrewd way to pay his $1,200 San Francisco apartment rent. He would offer “Air bed and breakfast”, which consisted of three airbeds,...

Airbnb® is an American company operating an online marketplace for lodging, primarily for vacation rentals. The purpose of this study is to perform an exploratory data analysis of the two datasets containing Airbnb® listings and across 10 major cities. We aim to use various data visualizations to gain valuable insight on the effects of pricing, covid, and more!

This repository contains supplementary materials for the article:

Determinants of Airbnb prices in European cities: A spatial econometrics approach

(DOI: https://doi.org/10.1016/j.tourman.2021.104319)

The materials include the used datasets and Python scripts for spatial regression models.

Datasets

For each city two files are provided: data for weekday and weekend offers

The columns are as following:

• realSum: the full price of accommodation for two people and two nights in EUR
• room_type: the type of the accommodation
• room_shared: dummy variable for shared rooms
• room_private: dummy variable for private rooms
• person_capacity: the maximum number of guests
• host_is_superhost: dummy variable for superhost status
• multi: dummy variable if the listing belongs to hosts with 2-4 offers
• biz: dummy variable if the listing belongs to hosts with more than 4 offers
• cleanliness_rating: cleanliness rating
• guest_satisfaction_overall: overall rating of the listing
• bedrooms: number of bedrooms (0 for studios)
• dist: distance from city centre in km
• metro_dist: distance from nearest metro station in km
• attr_index: attraction index of the listing location
• attr_index_norm: normalised attraction index (0-100)
• rest_index: restaurant index of the listing location
• attr_index_norm: normalised restaurant index (0-100)
• lng: longitude of the listing location
• lat: latitude of the listing location

Programming Scripts

In this repository you will find a script for spatial regressions in Python using PySAL (models_robust.py).

The codes cover the following regression models:

• OLS
• SLX (lagged_x)
• SAR (lagged_y)
• SDM (lagged_x_y)
• SEM (lagged_e)
• SDEM (lagged_e_x)

Main parameters:

• cities - list of cities from the dataset to be included in the analysis
• Robust=False: calculate the OLS, SLX, SAR and SDM regressions with W (weight matrix) based on 10 closest neighbours
• Robust=True: calculate all regression models with different specifications of W
• direct_indirect=True: calculate the direct and indirect effects (based on Golgher, A. B., & Voss, P. R. (2016). How to Interpret the Coefficients of Spatial Models: Spillovers, Direct and Indirect Effects. Spatial Demography (Vol. 4). https://doi.org/10.1007/s40980-015-0016-y)

Key functions:

• create_weights - defines the W specification
• write_stats - calculates's Moran's I and Geary's C
• direct - calculates the direct effect of the variable
• indirect - calculates the indirect effect
• coord - sets the coordinate refence system (CRS) appropriate to the analysed city
• total_results calculates the regressions
• the coordinates are projected from GPS (epsg:4326) to the local CRS (km_lat, km_lon)
• all regressions are saved as formatted txt table
• the results can be also saved as csv table

Context

Since 2008, guests and hosts have used Airbnb to travel in a more unique, personalized way. As part of the Airbnb Inside initiative, this dataset describes the listing activity of homestays in Boston, MA.

Content

This data file includes all needed information to about the listing details, the host, geographical availability, and necessary metrics to make predictions and draw conclusions. Basic data cleaning has been done, such as dropping redundant features (ex: city) and converting amenities into a dictionary. The data includes both numerical and categorical data, as well as natural language descriptions.

Acknowledgements

This dataset is part of Airbnb Inside, and the original source can be found here.

Inspiration

• Listing visualization
• What features drive the price of a listing up?
• What can we learn about different hosts and areas?
• What can we learn from predictions? (ex: locations, prices, reviews, etc)
• Which hosts are the busiest and why?
• Is there any noticeable difference of traffic among different areas and what could be the reason for it?

In New York City, one of the United States’ most iconic destinations, Airbnb has established itself as a key player in the accommodation market. In 2025, Airbnb customers booked an average of ** nights per stay, with an average price of *** U.S. dollars per night. Meanwhile, the average income per property was ***** U.S. dollars that year. Are Airbnb rentals expensive in New York City? As of early 2024, the most expensive Airbnb properties per night in the United States were in *************. This was followed by *************************. In comparison, the average cost of a night’s stay at an Airbnb property in New York City is less than half of the cost of a night in *************. How many Airbnb properties are there in New York City? In early 2024, the Airbnb market in New York City offered more than **** thousand properties accommodating to the different needs of visitors to the city. There are various types of Airbnb properties in New York City, the most common of which were entire homes and apartments, followed by private rooms. The majority of Airbnb listings also catered for longer-term stays, in light of city regulations on housing.

A list of buildings excluded from short-term rental activity under the Shared Housing Ordinance. See https://www.cityofchicago.org/city/en/depts/bacp/provdrs/bus/alerts/2016/july/Prohibited_Buildings_List_Affidavit.html for more information on the exclusion process.

The year-over-year growth in Airbnb reviews in several cities in the United States was affected by the coronavirus (COVID-19) pandemic in 2020. Year-on-year growth in all cities shown dropped below 50 percent by week 14 in 2020. Airbnb reviews in New York showed more of a decline during the pandemic than in the other cities, where growth rose above 50 percent again by week 30. While all cities showed upward turn by week 34, only Big Bear Lake and Galveston had a YoY growth of over 100 percent.