
Ask HN: What is the best NLP API/library for sentiment/emotional analysis? - wu-ikkyu
What is the best, preferably free&#x2F;open source, NLP API&#x2F;library out there for sentiment, emotional, concept, and keyword analysis?<p>I&#x27;m currently designing an application which will run NLP on daily journal entries in order to gain a personal meta psychological analysis over time.<p>Because of the potentially sensitive&#x2F;private nature of the journal entries, privacy is a very important consideration.<p>Thank you in advance.
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syllogism
What you're asking for can't really exist. If it could I'd provide it for you
in spaCy.

There's not really any such thing as "sentiment". You can classify reviews as
positive or negative, and then train a model to reproduce those annotations
pretty accurately. But a model trained to do that is unlikely to do anything
useful for your task --- the knowledge for your task is quite different.

You need to create some labelled data and train your own text classification
model. There are tonnes of tools for this. Scikit-Learn, Fast-Text and Vowpal
Wabbit are all good places to look, for different use-cases.

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wu-ikkyu
>There's not really any such thing as "sentiment". You can classify reviews as
positive or negative, and then train a model to reproduce those annotations
pretty accurately.

Here's an example of what I'm looking for in terms of sentiment and emotion.

[https://natural-language-understanding-demo.mybluemix.net](https://natural-
language-understanding-demo.mybluemix.net)

Journal entries can be given an overall positive/negative sentiment rating and
then plotted on a line graph over time.

Drops in positivity could then be further analyzed by looking at the keywords
and concepts of the affected time period.

Similar analysis could be done with the emotional analysis (i.e. joy, anger,
fear).

I've input a couple test journal entries into that example and it seems
feasible, but I'm looking for something free and/or that I could host myself
though I realize I may be asking for more than I can get.

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syllogism
You can train a system like this using free tools, but you need the training
data.

I'm not sure how IBM trained this system. Honestly I find the accuracy here
pretty indistinguishable from chance --- I think there's a strong Barnum
effect here.

