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You could break the text up into sentences [1] and do sentiment analysis [2] on the sentences with 'remote' in. Then flag based on that.

[1] https://opennlp.apache.org/documentation/1.5.3/manual/opennl...

[2] http://nlp.stanford.edu/sentiment/



Wikify it.

Let users can log in and change the remote/non-remote status (and other attributes).

Have some kind of trust system (could be linked to HN points or whatever).

(Even better if the YC guys made a custom job board where you fill in a form with all the details so there is no inconsistency.)


Or you could hire people to do it via oDesk or Mechanical Turk. Not so interesting technically, but it's a job people are good at.


Hire people for cheap to help people be hired for $$$, with no reward for the upsell. Brilliant! :)


Sentiment analysis probably isn't the right option here, though it may work.

I think a combination of dependency parsing[1] and regex is the way to go.

regex examples: "Remote: No", "No remote please"

Dependency parsing examples: ""Remote work isn’t an option", "Remote work will not be considered"

[1] look for negation in the parse tree using something like http://demo.ark.cs.cmu.edu/parse?sentence=Remote%20work%20is...


Sentence segmentation and sentiment analysis may be overkill.

N-grams + Naive Bayes is potentially Good Enough.




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