Submitted by Jeff Catlin on Thu, 05/31/2012 - 15:28
I recently attended the Sentiment Symposium in NYC that Seth Grimes puts on a couple of times per year.
Submitted by Seth Redmore on Thu, 05/17/2012 - 17:49
I analyzed 98,000 tweets, roughly the past 5 days worth of traffic for anything mentioning facebook and (ipo OR stock).
Submitted by Seth Redmore on Thu, 05/10/2012 - 20:36
I ran some analysis on about 330,000 tweets having to do with people going to see/having seen The Avengers. In case you've been completely deprived of any sort of media recently, it's a superhero movie.
Some might say "The Superhero Movie", but, not having seen it myself yet, I'm not in a position to judge.
Submitted by Seth Redmore on Tue, 04/03/2012 - 11:37
Submitted by Seth Redmore on Mon, 03/26/2012 - 10:30
Hi! Concept Topics are our revolutionary way to create classifiers for what used to be hard-to-classify buckets. Things like politics, food, real-estate, business. Most of our customers need to do some sort of classification - bucketing responses on surveys, determining which area of business is being talked about in the press.
Submitted by Seth Redmore on Wed, 02/29/2012 - 21:38
Submitted by Jeff Catlin on Mon, 02/13/2012 - 19:40
I’ve long believed that Text Analytics was going to “pop” one day and start showing up in all sorts of applications. I talked with a company yesterday that made me believe that day may be coming soon.
Submitted by Seth Redmore on Wed, 02/08/2012 - 15:28
I'm going to write a few blog articles to show how machine learning and natural language processing techniques are used in partnership inside of Lexalytics software.
What is Machine Learning?
Submitted by Jeff Catlin on Tue, 01/24/2012 - 07:47
So I watched an interesting video on some of the mechanically automated editorial work that is happening on major sites like Google and Facebook (see the video here: http://www.youtube.com/watch?v=bOE1HF
Submitted by Seth Redmore on Mon, 11/07/2011 - 02:12
In honor of the Sentiment Analysis Symposium this week in San Francisco (you are going to be there, right?), here's a summary of best practices for tuning sentiment. These will work for any sentiment analysis system, but you should use ours.
Because it's the best, 'natch.
1) 2 datasets: Gather a set of documents and split it in half.