Which classification to choose?

Question

I have huge amount of yelp data and I have to classify the reviews into 8 different categories.
Categories

Cleanliness
Customer Service
Parking
Billing
Food Pricing
Food Quality
Waiting time
Unspecified

Reviews contains multiple categories so I have used multilable classification. But I am confuse how I can handle the positive/negative . Example review may be for positive for food quality but negative for customer service. Ex- food taste was very good but staff behaviour was very bad. so review contains positive food quality but negative Customer service How can I handle this case? Should I do sentiment analysis before classification? Please help me

Answer 1

I think your data is very similar to Restaurants reviews. It contains around 100 reviews, with varied number of aspect terms in each (More information). So you can use Aspect-Based Sentiment Analysis like this:

1-Aspect term Extraction

Extracting the aspect terms from the reviews.

2-Aspect Polarity Detection

For a given set of aspect terms within a sentence, determine whether the polarity of each aspect term is positive, negative.

3-Identify the aspect categories

Given a predefined set of aspect categories (e.g., food quality, Customer service), identify the aspect categories discussed in a given sentence.

4-Determine the polarity

Given a set of pre-identified aspect categories (e.g., food quality, Customer service), determine the polarity (positive, negative) of each aspect category.

Please see this for more information about similar project.

I hope this can help you.