Natural Language Processing
Sentiment classification, or sentiment analysis, uses machine learning to analyze text and detect emotion without human intervention.
Businesses use sentiment analysis to process text, understand it, and take action exactly as a human would.
It can identify things like context, sarcasm, malapropisms, anger, etc.
It generates reports on things like public opinion and customer satisfaction levels, so business can derive actionable insights from complex and messy data.
Companies frequently use sentiment analysis to improve customer support and automate tasks with quick turnarounds, which increases the capacity of their employees and reduces workload, resulting in saved time and money.
SPAR employs various methods (including deep learning, a subsection of machine learning), complex algorithms, and neural networks to train systems to run sentiment analysis and identify key data like a human would.
Your business can leverage sentiment analysis using machine learning to help in matters like analyzing public opinion, improving customer support, and automating tasks with quick turnarounds.
Save time and money, get real, actionable insights, and improve your decisions. Learn more about how Spar can help you get started with sentiment analysis today.