Airbnb will block some reservations to prevent New Year’s Eve parties

(Bloomberg) – Airbnb Inc. is banning some users from booking overnight rentals of entire properties as part of the home-sharing platform’s efforts to prevent parties on New Year’s Eve.

The company will ban bookings for customers without a positive account history or previous bookings on the platform, factors it considers likely for a party to occur, according to a statement Thursday. A reservation in the same area where a guest lives will also trigger a red flag. And, if the same guest tries to book a two- or three-night reservation, Airbnb will suggest they book a private room or a hotel. The restrictions will come into effect over the next New Year’s weekend in 11 countries, including the United States, Canada, Brazil, France, Spain and the United Kingdom.

These measures follow Airbnb’s formal codification of a party ban this summer, which began as a public health measure at the start of the pandemic. The company will introduce global booking filtering technology next year to help build trust and security between hosts and guests in hopes that more people will become hosts to provide a second source of income as the economy slows.

“If you have a positive history and you’ve been a booker and have planned a trip in advance, these types of trips are pretty safe,” said Naba Banerjee, director of trust products and operations at the San Francisco-based company. a meeting. “If the host is present, the chances of you casting a rager are minimal.”

New booking filtering features will use contextual cues, such as a newly created account, booking location and a user’s age to determine if they are trying to host a party. The company piloted a test of New Year’s Eve restrictions in eight countries last year and said 340,000 guests were blocked or redirected from a booking over the holiday. Airbnb estimates the restrictions led to a 56% drop in holiday party incident rates last year compared to 2020.

Machine learning is useful for preventing parties when hard and fast rules may be too blunt given the size of Airbnb’s community, Banerjee said. “At this scale, what we learn is that the rules aren’t to scale and the rules are too brutal,” she said. “Our models are trying to learn with the data we have.”

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