After sexual assault reports, TripAdvisor adds 'safety' filters for hotel bookings

Online travel and restaurant booking site TripAdvisor will introduce new safety filters after people who used the site raised concerns over sexual assaults. TripAdvisor says it found 1,100 reviews that referenced sexual assault in just the last year alone.

The new search filter will show reviews that mention sexual assault or misconduct by employees of a business.

“This is a significant and promising change,” says Guardian reporter Rossalyn Warren.

Here's TripAdvisor's announcement.

TripAdvisor, which has about 456 million visitors a month, faced mounting pressure after Warren's previous reporting on this issue.

In March, Warren reported about concerns raised by women who said they were sexually assaulted by staff employees of hotels and businesses promoted on Tripadvisor.com.

It seems apparent that because of her report, they're making this much-needed change.

Here's an excerpt from her latest report:

The first feature the company is introducing is a new “traveller safety review” filter. The feature will allow people to search reviews that contain reports of safety-related incidents at hotels and businesses, and will be available in all 28 languages in which TripAdvisor is available.

For reviews posted in the last year, the filter will list reviews concerning sexual assault or misconduct by employees of a business. TripAdvisor said it found 1,100 reviews concerning sexual assault from the last year alone. The company said it would introduce a filter for other safety categories later.

From now on, the feature will filter all new reviews concerning multiple safety issues, including sexual assault, death, drugging, sex trafficking, armed robbery, and physical assault.

In a second safety feature, the company will insert a notice at the top of each review mentioning safety information, intended to make it easier for travellers to distinguish these from other reviews.

TripAdvisor said it would use a mix of employees and technology to identify reviews concerning safety. Over time, the company expects its machine learning algorithms to improve the capture rate of this information. All reviews on the site go through keyword filters to identify serious safety issues, such as sexual assault, and then are evaluated by human moderators to ensure they are appropriately categorised.

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