Name: Oded Netzer: Text Mining Social Media for Consumer Insights by Columbia Ideas at Work in textminingNLP
Duration: 15 min 12 s
Description: Professor Oded Netzer discusses how the emerging science of text mining is helping marketers measure their impact — and the surprising insights the field may offer the healthcare industry.

textminingNLP

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Every day, companies see thousands of emails, texts, tweets and other documents, but all the data in the world is useless if a company doesn't know what to do with it or if they can't quickly take action based on insights, opportunities and even potential disasters hidden among the data. Attensity reveals and analyzes these insights in real-time for businesses to make smarter, faster decisions across the enterprise. 

Don’t search for insights. Discover them with Attensity.


Discover the Value of Text Analytics

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Eric Volmar is teaching lead at the Gordian Knot Center for National Security Innovation at Stanford. His work focuses on connecting defense, academia, and entrepreneurship to accelerate innovation for national security, supporting new ventures at the intersection of technology and policy. In this presentation – followed by a conversation with Tina Seelig, executive director of Knight-Hennessy Scholars and director emerita of the Stanford Technology Ventures Program – Volmar advises entrepreneurs about how to navigate a new landscape shaped by a shift to deep tech, blended capital, and governments reengaging with technology innovation.

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Eric Volmar (Stanford University) - A New Entrepreneurship Playbook

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It seems like every day there's more and more machine learning problems that involve learning on text data, but text itself makes for fairly lousy inputs to machine learning algorithms.  That's why there are text vectorization algorithms, which re-format text data so it's ready for using for machine learning.  In this episode, we'll go over some of the most common and useful ways to preprocess text data for machine learning.

Feature Processing for Text Analytics

In this episode, we interviewed [Peter Murray Rust](https://twitter.com/thecontentmine?lang=en), chemist at Cambridge University. Peter is also known for his work and support related to open access and open data, among his projects is the [Content Mine](http://contentmine.org/) software chain about which we talked in this episode. The Content Mine group currently offer and maintain these open source software, but it also offers consulting services to assist individuals or groups interested in the suite of software.

Content Mine is a suite of open source software designed to mine and analyze the scientific literature. Three packages are currently offered by the [Content Mine group](https://github.com/ContentMine): getpapers, ami and norma. These 3 packages should allow us to download large sets of papers about a certain subject, normalize the obtained data to better explore it and then start analyzing using basic tools such as word counts and regular expressions. We explored and discussed these packages and how they could serve a researcher. You will also learn about the history of ContentMine, its team and the opinion of publishers, such as Elsevier, regarding such practices.

Blogpost: http://blog.colperscience.com/contentmine

Content Mine: scientific literature exploration through text mining

Episode 14: Content Mine: scientific literature exploration through text mining

Professor Oded Netzer discusses how the emerging science of text mining is helping marketers measure their impact — and the surprising insights the field may offer the healthcare industry.

Oded Netzer: Text Mining Social Media for Consumer Insights

Columbia Ideas at Work is a bridge between business research and practice, offering key insights from Columbia Business School’s faculty in a format that is easily accessible to busy executives.

Oded Netzer: Text Mining Social Media for Consumer Insights

Columbia Ideas at Work

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