articleJun 28, 2009Closed access
Meme-tracking and the dynamics of the news cycle
Stanford University · Cornell University
Indexed incrossref
Abstract
Tracking new topics, ideas, and "memes" across the Web has been an issue of considerable interest. Recent work has developed methods for tracking topic shifts over long time scales, as well as abrupt spikes in the appearance of particular named entities. However, these approaches are less well suited to the identification of content that spreads widely and then fades over time scales on the order of days - the time scale at which we perceive news and events.
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Authors
3Topics & keywords
Topics
Keywords
- Tracking (education)
- Computer science
- Dynamics (music)
- Identification (biology)
- Scale (ratio)
- Data science
- Artificial intelligence
- Cartography
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