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Cornell Research Study: Optimizing Web Traffic via the Media Scheduling Problem

Optimizing Web Traffic via the Media Scheduling Problem. Lars Backstrom, Jon Kleinbergy, Ravi Kumar, 15th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2009: “Website traffic varies through time in consistent and predictable ways, with highest traffic in the middle of the day. When providing media content to visitors, it is important to present repeat visitors with new content so that they keep coming back. In this paper we present an algorithm to balance the need to keep a website fresh with new content with the desire to present the best content to the most visitors at times of peak traffic. We formulate this as the media scheduling problem, where we attempt to maximize total clicks, given the overall traffic pattern and the time varying clickthrough rates of available media content. We present an efficient algorithm to perform this scheduling under certain conditions and apply this algorithm to real data obtained from server logs, showing evidence of significant improvements in traffic from our algorithmic schedules. Finally, we analyze the click data, presenting models for why and how the clickthrough rate for new content declines as it ages.”

  • New York Times: Study Measures the Chatter of the News Cycle – “For the most part, the traditional news outlets lead and the blogs follow, typically by 2.5 hours, according to a new computer analysis of news articles and commentary on the Web during the last three months of the 2008 presidential campaign.” See also Picturing the News Cycle Graphic
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