UNIVERSITY PARK, PA – People around the world paint their walls different colors, buy plants to beautify their interiors, and engage in a variety of other beautification techniques to personalize their homes, which has inspired a team of researchers to study approximately 50,000 pieces to be lived across the globe.
In a study that used artificial intelligence to analyze design elements, such as artwork and wall colors, in living room images posted on Airbnb, a popular home rental website, researchers found that people tended to follow cultural trends when decorating their interiors. In the United States, where researchers had economic data from the U.S. census, they also found that people from all socioeconomic groups made similar efforts in interior design.
âWe were interested in seeing how other cultures decorated,â said Clio Andris, assistant professor of geography, Penn State and associate at the Institute for CyberScience. âWe see maps of the world and we wonder, ‘What is it like to live there,’ but we don’t really know what it is to be in people’s living rooms and in their homes. It was as if people from all over the world were inviting us to their homes.
The team examined living room decor in 107 cities on six continents and in neighborhoods in six US cities.
Some regions seemed to have similar tastes when it comes to interior design, said Xi Liu, a geography doctoral student, Penn State and lead author of the study. In some cases, the way these cultures decorated their living rooms matched researchers’ expectations, he added.
âThere were a lot of bright colors in India and Morocco, for example,â Liu said. “And, of course, that wasn’t a big surprise – we had an idea that it might be the case before we started the study, but we weren’t sure whether that would be true or not.”
In Europe, North America and South America, people tended to post more books, the researchers said. Living rooms in Europe, especially Italy, featured a lot of wall art, which met their expectations.
However, the researchers, who published their findings in the current issue of EPJ Data Science, were surprised when some cultures objected to the way their living spaces are typically depicted on TV shows and travel brochures.
âWe found it interesting to find a lot of houseplants in cold areas, especially in Scandinavia,â said Andris. âWe initially thought there would be more houseplants in warmer regions because they would be inexpensive to have there, but that wasn’t the case. We were also surprised to find that many island cultures were a bit more austere than we initially thought. They didn’t use such vivid colors. Interiors in places like Fiji and the Caribbean, for example, were very clean. “
In the United States, researchers did not find a significant difference in the presence of decorative elements between neighborhoods with varying incomes, unemployment rates, education levels, residential property values, and racial diversity. . They suggest this indicates that Americans are making similar efforts to personalize their homes.
Because the task of flipping through a million images to note several decorative elements would take too long for the researchers, the team used deep learning, a type of artificial intelligence, to detect decorative objects, such as murals, plants, books and paint colors, in pictures. Human trainers first chose decorative elements in pictures to program the computer to recognize the decorations, and then the computer could choose and rank these features itself.
âThe term for this is transfer learning, but it’s a two-step process,â Liu said. âThe first step is to classify the images into categories, such as living rooms, kitchens, bedrooms and also outdoor space. Then we use object detection. The program will draw boxes around the objects in the rooms. , like wall art and books, then the program counts how many of those objects we have in each picture. “
The researchers only analyzed the living rooms of houses, as these rooms most likely represent the tastes of the owners and not just how they market their home on the rental website.
“In these websites you have a lot of pictures of rooms – and because they rent rooms we thought there might be a bias because the owner would like to decorate it in a certain way to appeal to the guests. guests, âLiu said. “But, we thought the living room would be more objective because the owner lives there and probably uses the space all the time.”
The researchers used an application programming interface – or API – that allowed them to access large amounts of publicly available data, including images, on Airbnb. They collected around a million geotagged images of the interior spaces of the site.
Andris said the study is also unique in that it may represent new ways for machine learning techniques to study cultural phenomena.
In the future, researchers may look to other online photo centers, such as Craigslist, to better target natural decorative tastes. They can also train the computer program to detect styles of artwork or other significant objects, such as flags, pictures of world leaders, or historical emblems.
Liu and Andris also worked with Zixuan Huang, graduate assistant in geography, University of Utah, and Sohrab Rahimi, doctoral student in architecture, Penn State.