Tom Zeng ( & Dave Naffis)
Tweet Sentiment Analysis using Machine Learning and Natural Language Processing
In this talk, we will go through some Sentiment Analysis basics, and we will then focus on analyzing tweets using Machine Learning and Natural Language Processing technologies, we will survey the open source and commercial ML and NLP tools in general and cover the Support Vector Machines classification models and the OpenAmply NLP APIs in particular. We will discuss the potential applications of tweet sentiment analysis with real world examples (brand monitoring: Comcast vs Verizon, event monitoring: noticeably negative sentiment when Michael Jackson passed away, and positive sentiment index during Christmas). We will conclude with some discussion on techniques for analyzing large realtime data stream like Twitter and Q & A.
About Tom Zeng ( & Dave Naffis):
Tom Zeng is a software architect with the Washington DC based Ruby on Rails development firm Intridea Inc. He's interested researching the latest technologies and applying them to real world problems. Tom has many years of development experiences in the financial(Footprint Software/IBM Canada), ecommerce(Ironside, Spaceworks), and enterprise risk management(iJET) software applications using Java and Ruby on Rails, he holds a Masters of Applied Sciences degree from the University of Waterloo, ON, Canada.
Dave Naffis is the cofounder of Intridea and a classic Web 2.0 "hacker". As Intridea's lead Architect, and an expert Ruby on Rails developer, Dave heads the product development efforts. He is an active member of the Rails community and the author of numerous plugins. Before Intridea, Dave spent years at both AOL and IMAKE and received a Masters in Systems Engineering from the University of Virginia. In other entrepreneurial ventures, Dave built and operated CanYouConnect - a social-networking site that competed with MySpace - and Connexon Media - a Rails consultancy. Dave also helped found the Washington DC Ruby User Group.
