Jason S. Kessler

Jason Kessler

  Mistaken identity
If you've ever wondered what it's like to have the name Jason Kessler, check out this December 2017 New Yorker article.
Jason Kessler is a Machine Learning Engineer at Amazon Web Services, in Seattle WA. Prior to AWS, he was a lead data scientist at CDK Global, where he analyzed language use and consumer behavior in the online auto-shopping ecosystem. Before CDK, Jason was the founding data scientist at PlaceIQ and worked as a research scientist for JD Power and Associates. He has published peer-reviewed papers on algorithms and corpora for sentiment and belief analysis, and has sat on program committees and reviewed for several AI and NLP conferences. Most recently, he has conducted research on identifying persuasive and influential language and the visualization of differing corpora.
Video of my talk on Scattertext
Publications: Blog posts: Talks: Unpublished Papers: Popular and Trade Press Data and Software
  • Scattertext, a Python term importance and text visualization package.
  • Age from Name, a Python package to estimate a person's age and generation from their name and gender.
  • You may request the JDPA Sentiment Corpus (used in Kessler and Nicolov [2009] and Kessler et al. [2010]) through the official website.
  • The lexicon of terms and multi-word units organized by part-of-speech, veridicality (including facticity) can be found here. These terms, when selected for by syntactic templates outlined in the ICWSM 2008 paper can be used to accurately predict the veridicity of an embedded, finite clause. This an important step in recognizing textual entailment and paraphrase.
Industrial Activities:
Machine Learning Engineer at Amazon Web Services, Seattle.
Lead (as of Sept. 2016) data scientist at CDK Global, Seattle.
Founding data scientist at PlaceIQ, NYC.
Adviser to Votizen, Mountain View, CA. (acquired by Causes)
Scientist at J.D. Power and Associates, Boulder, CO. Working with Dr. Nicolas Nicolov, I helped to guide the construction of a corpus for structural sentiment analysis and researched ways of automatically annotating structural sentiment relations. Please see our ICWSM 200 and, 2010 papers, as well as our recent Handbook of Linguistic Annotation chapter for details on this effort.
Summer of 2009:
Research Intern at Palo Alto Research Center (formally Xerox PARC). I worked on a project in sentiment analysis as a member of the Computing Sciences Lab.
Service: Contact: Academic Activities:
Ph.D. candidate in Computer Science at Indiana University, Bloomington. My research focused on applying statistical natural language processing techniques for sentiment analysis. Specifically, I explore the compositional way that evaluations is expressed toward discourse entities, a topic my collaborators and I call "structural sentiment."
In 2005, I received a B.S. in Computer Science from the University of Pittsburgh. While an undergrad, I worked on OpinionFinder, a publicly available system for sentence and expression-level subjectivity analysis.
Tutorials: Distractions:
  • A map of Rome showing the location of each Borromini building in the city.
  • Richard Serra on Charlie Rose (14 December 2001)
  • The Linguist's Search Engine.
  • The Gallery of "Misused" Quotation Marks
  • SIL's glossary of linguistic terms.
  • My Erdös number is less than or equal to 5 (via Claire Cardie ~ Raymond J. Mooney ~ Wolfgang Maass ~ Andras Hajnal)
  • A slightly outdated guide by John "Verm" Sherman to the Hueco Scale for grading boulder problems.
This is a personal web site, produced on my own time and solely reflecting my personal opinions. Statements on this site do not represent the views or policies of my employer, past or present, or any other organization with which I may be affiliated.