October 22, 2013
Scientists Use Flickr To Predict Peak Park Seasons And Favorite Attractions
[ Watch the Video: Flickr Photos Will Help Study Tourism Spots ]
Michael Harper for redOrbit.com - Your Universe Online
The same information could be used to understand the popularity of any given tourist destination, including amusement parks, ball parks and museums. A similar study was conducted at Stanford in February to understand the economic value of coastal areas on neighboring communities. This new research was published in the latest edition of the journal Scientific Reports.
The idea behind this research is quite simple. Tourists are often quite shutter happy, snapping pictures of natural landscapes and park markers. The Stanford scientists with the Natural Capital Project simply sought out public pictures of these natural areas, recorded the metadata associated with these pictures (including date, time and exact location) and compiled this information.
Specifically, the group gathered 1.4 million geo-tagged photos on Flickr, then used information found in the photographers profile to determine how far they traveled to arrive at their destination. After applying this information to 836 recreational sites in the US and abroad, the scientists say this method of understanding who visits these attractions and for how long is both reliable and cost-effective. Those in charge of these parks and attractions can also use this data to predict surges in traffic as well as slow seasons.
"No one has been able to crack the problem of figuring out visitation rates and values for tourism and recreation without on-site studies until now," explained lead scientist at the Natural Capital Project Anne Guerry.
Previously, researchers had to either go into the campgrounds to perform surveys or station employees at the gates to get a count of how many visitors have entered. With social media, these parks directors can obtain a wealth of information - including the number of people who visit, the most common areas and attractions, and even how satisfied the tourists were with their visit - without the need for extra staff.
This kind of study can be carried out on the cheap with specially-designed software to scour publicly displayed information on the Internet. Armed with this data, land-use planners and government agencies can provide ample staffing for these attractions, repurpose money to improve the lesser visited areas of their parks, and more effectively run the entire operations.
This isn’t the first time social media has been used to make predictions, of course. Earlier this year, researchers at Boston Children’s Hospital discovered that they could predict geographic areas more prone to obesity by observing what people in these areas “liked” on Facebook. Areas which preferred television shows over outdoor activities, for instance, were more likely to be obese.