Inside Airbnb — Listing Data

Creators:

Murray Cox

Publication Date:

Ongoing since February 2015

Data Category:

Marketing and Advertising Social Media and Online Reviews

Dataset Description:

Inside Airbnb provides listing-level data scraped from publicly available information on Airbnb.com for cities worldwide. Each snapshot contains the listing title and full-text description, host attributes (e.g., Superhost status, verifications, experience), property characteristics (room/property type, capacity, amenities, price and fees, cancellation policy), quality ratings, and review counts. The data is well suited to text/emoji analysis and to modelling how listing content relates to demand and electronic word-of-mouth.

Variables:

Variable name	Variable definition
id	Unique numeric identifier of the Airbnb listing.
name	Listing title/headline shown in search results — the short promotional text (may contain words, symbols, and emojis).
description	Full free-text description of the property and host on the listing page (unstructured text).
host_id	Unique numeric identifier of the host.
host_since	Date the host joined Airbnb; used to derive host experience (years).
host_is_superhost	Indicator (t/f) of whether the host holds the Superhost badge.
host_verifications	List/count of identity verifications completed by the host.
host_listings_count	Number of listings managed by the host; used to flag professional (multi-property) hosts.
neighbourhood/neighbourhood_cleansed	Neighbourhood name/region of the listing.
latitude, longitude	Geographic coordinates of the listing.
property_type	Type of property (e.g., apartment, house).
room_type	Room category (e.g., "Entire home/apt", "Private room").
accommodates	Maximum number of guests the listing accommodates (capacity).
bedrooms, beds, bathrooms	Counts of bedrooms, beds, and bathrooms.
amenities	List of amenities offered; number of amenities is used as a control.
price	Nightly price in local currency.
security_deposit, cleaning_fee	Refundable deposit and cleaning fee charged, in local currency.
minimum_nights	Minimum number of nights required per booking.
instant_bookable	Indicator (t/f) of whether the listing can be booked instantly.
cancellation_policy	Cancellation policy category (e.g., flexible, moderate, strict).
number_of_reviews	Cumulative number of reviews received; successive differences give new reviews per period (paper’s eWOM-volume dependent variable).
reviews_per_month	Average number of reviews received per month.
review_scores_rating	Overall guest rating/quality score for the listing.
last_scraped	Date the listing page was captured; differences give "time since last scrape".
calendar / reviews (companion files)	Calendar file: date-level availability and price per listing. Reviews file: reviewer id, date, and full review text per listing.

Details:

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