MemeTracker builds maps of the daily news cycle by analyzing around 900,000 news stories and blog posts per day from 1 million online sources, ranging from mass media to personal blogs.
We track the quotes and phrases that appear most frequently over time across this entire spectrum. This makes it possible to see how different stories compete for news and blog coverage each day, and how certain stories persist while others fade quickly.
The plot above shows the frequency of the top 50 quotes in the news and blogs over time, during the U.S. presidential election. For more read our paper:
J. Leskovec, L. Backstrom, J. Kleinberg. Meme-tracking and the Dynamics of the News Cycle. ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, 2009.
C. Brooks, and N. Montanez. WWW '06: Proceedings of the 15th international conference on World Wide Web, page 625--632. New York, NY, USA, ACM Press, (2006)
J. Leskovec, L. Backstrom, and J. Kleinberg. KDD '09: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, page 497--506. New York, NY, USA, ACM, (2009)
B. Berendt, N. Glance, and A. Hotho (Eds.) Workshop at 18th Europ. Conf. on Machine Learning (ECML'08) / 11th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'08), (2008)