Sentiment analysis measures the feeling behind conversations about your brand. Mentions, comments and reviews are sorted as positive, negative or neutral, usually by software that reads the language used.
The result is often shown as a percentage split or a net sentiment score, calculated as positive mentions minus negative mentions, divided by total mentions. Watching that score over time shows whether a launch, campaign or crisis is shifting how people feel.
Automated tools are fast but imperfect. Sarcasm, slang and mixed opinions can confuse them, so sample real comments to check accuracy. A sudden spike in negative sentiment is a cue to investigate quickly and respond.
Questions about Sentiment Analysis
How is sentiment analysis done on social media?
Social listening or analytics tools collect mentions and comments, then use language models or keyword rules to label each one as positive, negative or neutral. Results are summarized in charts so you can track mood over time and by topic.
How do you calculate a net sentiment score?
Subtract negative mentions from positive mentions, then divide by total mentions and multiply by 100. For example, 60 positive, 20 negative and 20 neutral gives (60 - 20) / 100 x 100, a net sentiment of 40.
How accurate is sentiment analysis?
It's useful for spotting trends but not perfect. Tools can misread sarcasm, slang, emojis and mixed feelings. Accuracy improves with modern AI models, but regular human spot checks are still the best way to trust the results.
