Timothy Jurka | |
---|---|
Alma mater | University of California, Davis |
Known for | Contributions to document classification software |
Scientific career | |
Fields | Computer Science Political Science |
Timothy Jurka is a Polish-American computer scientist and political scientist.
Background
Jurka is best known for developing the artificial intelligence that ranks the LinkedIn news feed.[1][2] Previously, Jurka developed machine learning algorithms for news recommendations in the Pulse news reading application, which was acquired by LinkedIn in 2013.[3]
As a Ph.D. student at UC Davis, Jurka collaborated on numerous projects in political science spanning media framing,[4][5] civic engagement,[6] and tobacco and immunization policy.[7] Additionally, he wrote text classification software, including RTextTools and MaxEnt for the R statistical programming language.[8][9][10][11]
He is the son of computational biologist Jerzy Jurka.[12]
References
- ↑ LinkedIn "A Look Behind the AI that Powers LinkedIn’s Feed"
- ↑ Axios "LinkedIn goes niche"
- ↑ TechCrunch "LinkedIn Acquires Pulse For $90M In Stock And Cash"
- ↑ University of Chicago Press "Making the News: Politics, the Media, and Agenda Setting"
- ↑ Washington Monthly "College Students on the Debate: Agreeing with Obama, Agreeing that Romney Won"
- ↑ Social Science Research Network "Colleague Crowdsourcing: A Method for Incentivizing National Student Engagement and Large-N Data Collection"
- ↑ State Politics and Policy Conference "Agendas and Alternatives in the American States: Determinants of State Legislative Attention to Tobacco and Immunizations"
- ↑ Google Scholar "Timothy P. Jurka"
- ↑ The R Journal "RTextTools: A Supervised Learning Package for Text Classification"
- ↑ The R Journal "maxent: An R Package for Low-memory Multinomial Logistic Regression with Support for Semi-automated Text Classification"
- ↑ DataScience+ "Sentiment analysis with machine learning in R"
- ↑ Jurka, E. (2015). "Jerzy Jurka: June 4, 1950 – July 19, 2014". Mob DNA. 6: 2. doi:10.1186/s13100-014-0032-2. PMC 4293820.
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