Topic based sentiment is the application of sentiment analysis on a list of specific topics that are known ahead of time.
By restricting the scope of sentiment analysis to only specific topics, higher levels of precision, accuracy and insight can be achieved. Real-world text isn't always clean cut and straight-forward; often multiple topics are mentioned in one document with a mix of sentiment. Applying document-level sentiment in such a situation can lead to a loss of nuance and missed insight.
Use topic based sentiment analysis when it is known ahead of time which topics sentiment is required for.
Real-world text, like product reviews and survey responses, can be messy and unorganized. Your customers are expressing their opinions as they come to mind, mixing positive and negative sentiment. In order to truly understand what your customers like or dislike, it's import to zero in on individual topics and concepts.
Topic based sentiment isolates the sentiment for each topic and ensures that no nuance is lost. For each specific topic found in the text, Repustate calculates the sentiment and returns the numerical sentiment score on a sentiment visualisation dashboard.
When done across a large dataset, insights quickly surface and sentiments are unlocked for each topic of interest.
Topic based sentiment analysis is the ideal way to analyze sentiment when desired topics are known ahead of time.