Stanford Offers Free Machine Learning Tool

March 5, 2014

A team from Stanford is bringing machine learning to the masses, for free. Is this bad news for the for-a-fee text analytics vendors? Stanford Engineering announces, “Stanford Scientists Put Free Text-Analysis Tool on the Web.” Writers Andrew Meyers and Tom Abate explain:

“The etcML website is based on machine-learning techniques that were developed to analyze the meaning embodied in text, then gauge its overall positive or negative sentiment. To access this computational engine, users drag and drop text files into a dialog box. ‘We wanted to make standard machine learning techniques available to people and researchers who may not be able to program,’ said Richard Socher, a doctoral candidate in computer science at Stanford and lead developer of etcML. Socher said the new site gives researchers and citizen activists in fields ranging from political science to linguistics an easy way to analyze news articles, social media posts, closed-caption transcripts of television newscasts and other texts of possible interest.’All users have to do is copy and paste, or drop their text datasets into their browser and click,’ Socher said.”

Several Stanford-affiliated folks have already leveraged the beta version of etcML. Rebecca Weiss, who studies political polarization and media coverage in her doctoral work, uses the tool to classify words and phrases and to tease patterns from millions of articles and transcripts. Meanwhile, computational linguistics researcher Rob Voight has employed etcML to determine what factors make a Kickstarter pitch most successful. Computer science doctoral student Chinmay Kulkarni has also put the solution to good use; it helps him make short(er) work of test-grading for a free online course with about 2,000 students.

So, what will the general public make of this “free and powerful” drag-and-drop tool? I played around with it a bit, and the results are interesting. I think the team may still have some tweaking to do— I made a Twitter-sentiment-query on Elizabeth Warren (I know, my politics are showing), and it counted a tweet that read “Education is really important! More money for colleges! #Vote4Warren” as “negative.” Perhaps the for-profit machine learning vendors are safe for now. Check etcML out for yourself here and see what you think.

Cynthia Murrell, March 05, 2014

Sponsored by ArnoldIT.com, developer of Augmentext

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