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This site had posted approximately 2,807 videos to its YouTube channel that were viewed by 30 million users in 217 countries. The algorithms then identified unique ways that groups of people were interacting with the information, in this case, news videos. News site editors could use this information to better collect and target content to these audiences, said Jansen, who worked with Haewoon Kwak, research scientist and Jisun An, postdoctoral researcher, both of Qatar Computing Research Institute, Hamad Bin Khalifa University. "Journalists want to have a better understanding of just who their actual users are," said Jansen. "They can use that information to reach readers with better titles, content and article framing." While the researchers used news and information in this study, the technology could be applied to other types of consumer transactions, according to the researchers, who presented their findings on Dec. 2 at the Second International Workshop on Online Social Networks Technologies held in Agadir, Morocco. "The method is transferrable to other domains," said Jansen. "It could work at any consumer touchpoint - any place where we can see what the consumers are buying or what they are viewing before they buy and then tie it back to some demographics." Jansen said the technology is also scalable and could use other types of social media to här analyze consumer behavior and create marketing personas. "We're now scaling this up to millions of users," he said. "And we could use other types of social media data, from Facebook or Twitter, for example." ### Disclaimer: AAAS and EurekAlert!
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