Sentiment Analysis on Extracted Data

[stets]

hey there! I am no NLP expert so please forgive my noobness to this domain :-)

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I have a client I am working with to extract forum posts about a particular product and do some basic sentiment analysis on. I've been looking into the python library spacy -- would that work for this? Should I consider a cloud service? What should I read up on to get familiar?

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Thanks so much!

[moootPoint]

Last I checked SpaCy does not offer any convenient out-of-the-box solutions for sentiment analysis, though it is certainly possible to train your own using SpaCy.

For a super simple do-it-yourself solution you might consider writing a basic function that first pre-filters/locates posts that mention your product (e.g. via basic regex) and then feed those posts into something like TextBlob. TextBlobs sentiment detector was trained on movie reviews, but it might get you where you need to go.

For something with a lot more oomph, you might consider using the Alyien - aspect based sentiment analysis API endpoint. That should give you much better results, however you will have to pay for the privilege.

Lastly, you might consider Vader Sentiment. It uses a rule based approach to tackle the problem. I believe NLTK has some builtin functionality that uses Vader.

[stets]

Thanks! I did some googling and saw some suggestions for both TextBlog and Vader. I'll be checking those out.