What are the most challenging issues in Sentiment Analysis(opinion mining)?
January 28, 2011 Leave a comment
Ramy Ghaly January 28, 2011
The key challenges for sentiment analysis are:-
2) Anaphora Resolution – the problem of resolving what a pronoun, or a noun phrase refers to. “We watched the movie and went to dinner; it was awful.” What does “It” refer to?
3) Parsing – What is the subject and object of the sentence, which one does the verb and/or adjective actually refer to?
4) Sarcasm – If you don’t know the author you have no idea whether ‘bad’ means bad or good.
5) Twitter – abbreviations, lack of capitals, poor spelling, poor punctuation, poor grammar, …
I agree with Hightechrider that those are areas where Sentiment Analysis accuracy can see improvement. I would also add that sentiment analysis tends to be done on closed-domain text for the most part. Attempts to do it on open domain text usually winds up having very bad accuracy/F1 measure/what have you or else it is pseudo-open-domain because it only looks at certain grammatical constructions. So I would say topic-sensitive sentiment analysis that can identify context and make decisions based on that is an exciting area for research (and industry products).
I think the answer is the language complexity, mistakes in grammar, and spelling. There is vast of ways people expresses there opinions, e.g., sarcasms could be wrongly interpreted as extremely positive sentiment.
What do you think? Do you agree? Would you like to ask a question and get an answer? Try out: