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Social media posts get popularity boost with new algorithm

Image credit: Milkos | Dreamstime.com

Computer scientists from the University of Tokyo have created an algorithm that recommends tags for social media posts which should boost their popularity.

Xueting Wang, a keen user of social media sites and a postdoctoral researcher at the Yamasaki Laboratory, was curious by how different posts by different people achieve notoriety or fade into obscurity.

Driven by this curiosity, Wang, her colleague Yiwei Zhang and their supervisor, associate professor Toshihiko Yamasaki, investigated the relationship between social media content, the tags attached to content and the people who post it.

“It is well-known in our field that tags for social media posts are important,” Wang explained. “It’s also known that the nature of these tags, and the relative popularity of the user in question, can impact the popularity of a post – for example, the number of views.

“What I wanted to do was come up with a system to recommend suitable tags for your posts that would demonstrably improve their popularity,” she added.

Although computers are exceptional at precisely defined mathematical tasks, the researchers found that some of the social media concepts explored, such as a user’s popularity, are too vague for a computer to process directly.

To overcome this challenge, Wang and the team had to carefully define every aspect of the problem in mathematical terms for an algorithm to be possible.

Wang said: “We had 60,000 publicly available images with tags, number of views and associated user data from photography website Flickr to experiment with.

“That gave us enough source data to make a system to score different user and image details and assign numerical values to things. This meant we could perform different functions on the data.”

The team used this data to rank the effective success of a specific tag in contributing to the images view-count. As part of its outcome, successful tags were recommended by this process that resulted in a 20 per cent boost to the popularity of a post.

The Japanese researchers, however, have argued that what sets their approach apart from other studies is that the algorithm takes into account who created the post. Furthermore, the system imitates the tagging behaviour of people with high social-popularity scores to recommend effective tags.

“The algorithm is called the ‘user-aware folk popularity rank’ and it is the first of its kind to be, as the name suggests, aware of the user in how it recommends tags,” said Wang.

“We see from our results that carefully selected tags which express emotional impressions rather than just literal representations of the image content will be more effective.

“But all the tags the system produces are from an existing pool and it would be good to grow our system so it can generate new ideas.”

According to the researchers, their findings could have potential in the commercial world and can be used by other researchers who study online behaviour.

Furthermore, Wang said she intends to improve the effectiveness of the system as well as implement greater autonomy so it can generate tags of its own. She also hopes social media researchers could use these ideas to explore things such as what makes a user popular online to begin with.

The study, ‘User-Aware Folk Popularity Rank: User-Popularity-Based Tag Recommendation That Can Enhance Social Popularity, has been published in the 'Proceedings of the 27th ACM International Conference on Multimedia' paper.

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