I've been reading Bing Liu's book on Sentiment Analysis. He mentions all of these slightly different approaches seen in research since 2004, but doesn't talk much about efficacy at all.That leaves me - someone who has not done any sentiment analysis before - wondering what approaches are seeing the best results currently. And it specifically needs to be an approach that can extract the sentiments of individual topics found in the text, not just if a document/sentence is positive or negative.In case it makes a huge difference: the object of analysis will be reddit comments, not tweets or reviews which seem to be the most common source of data.
What is the current state-of-the-art within aspect-based sentiment analysis?
machine learning;nlp;sentiment analysis