Despite advancements in natural language processing (NLP) technologies, understanding human language is challenging for machines. They may misinterpret finer nuances of human communication such as those given below.
Sarcasm
It is extremely difficult for a computer to analyze sentiment in sentences that comprise sarcasm. Consider the following sentence, Yeah, great. It took three weeks for my order to arrive. Unless the computer analyzes the sentence with a complete understanding of the scenario, it will label the experience as positive based on the word great.
Negation
Negation is the use of negative words to convey a reversal of meaning in the sentence. For example, I wouldn't say the subscription was expensive. Sentiment analysis algorithms might have difficulty interpreting such sentences correctly, particularly if the negation happens across two sentences, such as, I thought the subscription was cheap. It wasn't.
Multipolarity
Multipolarity occurs when a sentence contains more than one sentiment. For example, a product review reads, I'm happy with the sturdy build but not impressed with the color. It becomes difficult for the software to interpret the underlying sentiment. You'll need to use aspect-based sentiment analysis to extract each entity and its corresponding emotion.