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Comment by sixQuarks | Hacker News Reader

Can someone explain what this does in layman's terms? I'm a biz guy, not a coder, but I'm interested in the use cases. thanks

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This is an extension to the Python programming language that makes it easier to analyze and manipulate text.

For example, an analyst might use sentiment analysis to see whether Facebook posts about a product are "positive" or "negative" in tone.

As another example, I hacked together this online sentiment analyzer using TextBlob: https://textfeel.herokuapp.com/

See also: NLP (Wikipedia): https://en.wikipedia.org/wiki/Natural_language_processing NLTK (a python library for NLP): http://nltk.org/ Twitter opinion mining using pattern: http://www.clips.ua.ac.be/pages/pattern-examples-elections

OK, so it's mostly to analyze text that's already been written? Can it also write natural language text based on data inputs?

> Can it also write natural language text based on data inputs?

from the features list it doesn't seem to.

What you're referring to is text generated using a Markov Chain algorithm. This will generate text that seems at first glance to be human generated. On closer inspection you'll find that it only follows common linguistic patterns, the actual content is gibberish.

This sounds interesting. Can you specify an example usecase (what would be the input data and how would generated natural language look like), and I will try to see if I can do it.

For example, financial data would be used as input to generate a daily stock market overview. Something along the lines of:

"Today, the Dow hit a high of 16,200, marking the first time it has crossed the 16,000 barrier. blah blah blah, etc"

Basically, use data points to create a market overview where readers wouldn't know that it was computer generated. That's one idea.

I think the only use case is spam. But it's a big one.

Natural language generation is also an NLP task, but this particular library doesn't seem to tackle it at the moment.

Good hack, now I'm following your github!

I'm having deja vu, do you post this in every NLP-related topic?

(posting before I commentstalk you to confirm, this is just as much to test my memory as anything else)

edit: maybe not...damn, I swear I've seen this exact phrase in several NLP threads

I wonder if an NLP-driven scraper could confirm your deja-vu... ;)

Nope, my first time asking this.

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