Comment on Show HN: Where is “Who is hiring?” hiring?parentComments−louthy11yYou 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/−bbcbasic11yWikify 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.)−davidw11yOr 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.−fudged7111yHire people for cheap to help people be hired for $$$, with no reward for the upsell. Brilliant! :)−nl11ySentiment analysis probably isn't the right option here, though it may work.I think a combination of dependency parsing[1] and regex is the way to go.regex examples: "Remote: No", "No remote please"Dependency parsing examples: ""Remote work isn’t an option", "Remote work will not be considered"[1] look for negation in the parse tree using something like http://demo.ark.cs.cmu.edu/parse?sentence=Remote%20work%20is...−WalterGR11ySentence segmentation and sentiment analysis may be overkill.N-grams + Naive Bayes is potentially Good Enough.
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You could break the text up into sentences [1] and do sentiment analysis [2] on the sentences with 'remote' in. Then flag based on that.
[1] https://opennlp.apache.org/documentation/1.5.3/manual/opennl...
[2] http://nlp.stanford.edu/sentiment/
Wikify it.
Let users can log in and change the remote/non-remote status (and other attributes).
Have some kind of trust system (could be linked to HN points or whatever).
(Even better if the YC guys made a custom job board where you fill in a form with all the details so there is no inconsistency.)
Or you could hire people to do it via oDesk or Mechanical Turk. Not so interesting technically, but it's a job people are good at.
Hire people for cheap to help people be hired for $$$, 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.