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As online advertising money starts shrinking in the economic downturn, some researchers are looking for ways to make the most of every single dollar. Recent research from HP Labs in Palo Alto, CA, shows that it’s possible to predict, with reasonable accuracy, how popular an online video clip or news story will become simply by looking at how well it does within the first few hours of being posted. If content providers can predict how many views a video or article will get over a set period, then they can match the most popular items with specific high-dollar ads. Additionally, content providers can place potentially popular content in eye-catching spots on their site, further increasing the number of people who see it and the accompanying ads.

“There’s an obvious byproduct of what we’re doing here for advertising,” says Bernardo Huberman, a senior fellow at HP who led the work. “This will allow people who advertise to at least start getting a sense of what they want […] if very early on you can tell if people will like a video or news story.”

Huberman and his colleagues looked at historical data gathered from the video site YouTube, and from Digg, a news aggregator that lets readers’ votes determine which stories become most prominent. The researchers applied mathematical models to these data sets, determining a “popularity curve” for different items. These curves allowed the researchers to extrapolate the future popularity of an item using only information about its popularity over the first few hours or days.

HP isn’t the only organization trying to predict the popularity of content. Researchers at Google, Yahoo, Microsoft, and IBM, to name a few, have all invested resources and money in researching the problem. A few years ago, Duncan Watts, now a researcher at Yahoo, showed that the quality of a song is a very poor indicator of its eventual popularity, and that long-term song popularity–as measured on music-sharing networks–can be determined fairly early on, when a sort of popularity trajectory is determined.

In the case of Digg, Huberman says that within the first few hours it is clear whether a story will become popular or not (depending on how many “diggs”–or votes–it receives from the site’s community of readers). Factoring in the time of day that a story is submitted (a noontime story will get, on average, twice as many early diggs as a story submitted at midnight), the researchers found that if a story receives a low number of diggs, it has relatively little hope of being one of the top viewed stories of the day. Conversely, if a story receives hundreds of diggs in the first hours, it’s likely to be much more popular.

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Credit: Technology Review

Tagged: Business, Web, HP, online advertising, predictive software, attention

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