New York / Washington / DC / Washington / D.C. / Prague / San Jose / /
Company
Twitter / Google / 10th ACM SIGKDD Intl / Pearson / New York Times / 11th ACM SIGKDD Intl / Reuters / /
Continent
Americas / /
Country
United States / /
Currency
pence / USD / / /
Event
Product Recall / Product Issues / /
Facility
University Department / U.S. Library of Congress / /
IndustryTerm
user-generated Web content / online data / Internet activity / Opinion mining / influenza epidemics using search engine query data / Web content / document classification algorithm / internet searches / online hate groups / micro-blogging site / web-based text mining system / data mining / social networking websites / pre-processing stage / web access logs / search history / food / Internet surveillance systems / social media / micro-blogging services / public health intelligence network / proposed solutions / Internet-based surveillance / online news media text / web search / search engine logs / electronic healthcare / online news sources / search engine / keyword selection systems / search term frequency / online chatter / /
Organization
Association for Machine Translation / Centers for Disease Control and Prevention / Congress / CDC’s ILINet / Louisiana Board of Regents / Southeastern Louisiana University Department of Computer Science Hammond / /
Person
Troy Kammerdiener / / /
Position
sentiment-aware model for predicting sales performance using blogs / Text Mining General / /
Product
Tylenol / Flu Trends service / drug / several Tylenol / Flu Trends / /
Towards detecting influenza epidemics by analyzing Twitter messages Aron Culotta Southeastern Louisiana University Department of Computer Science Hammond, LA 70402