Sentiment Analyzer
A Sentiment Analyzer is an AI tool that evaluates the emotions or tone in text. By analyzing words, phrases, and context, it identifies whether the text conveys a positive, negative, or neutral sentiment. This allows quick insights into how content might be perceived—whether it feels optimistic, critical, or factual. Such analysis is useful for understanding feedback, capturing customer sentiment, or assessing the impact of written communication. Try it. Add some text in the field below.
Demo
How it works
Prompt
Analyze the sentiment of the following text and return only a number between -1 and 1 with up to three decimal places (e.g., 0.125 or -0.585), where -1 is very negative, 0 is neutral, and 1 is very positive: TEXT
How to use
You can enter text in any language to analyze its sentiment, and the evaluation for each sentence begins in real-time as soon as you start typing. The tool processes each sentence individually, returning a sentiment score between -1 and 1, where -1 is highly negative, 0 is neutral, and 1 is highly positive. Results include precise scores with three decimal places, allowing for detailed insights into subtle tone variations. Simply enter your text to view the overall sentiment and, if you wish, click the 'Show Detailed Analysis' button to see a breakdown of each sentence's sentiment score. This tool is ideal for applications such as monitoring customer feedback, social media sentiment, product reviews, and more.
Use Case
There are numerous use cases for sentiment analysis, especially when it provides precise evaluations with fine granularity (such as three decimal places). Here are some of the most important application areas:
- Customer Satisfaction and Support: Analyze customer feedback and support tickets to gauge sentiment and identify issues early. Prioritize critical or negative responses for immediate attention.
- Social Media Monitoring: Track brand, product, or campaign sentiment in real time. Identify influencers and factors behind positive or negative reactions.
- Product and Service Reviews: Analyze online reviews to uncover areas for improvement in products or services. Fine sentiment values improve analysis accuracy in large datasets.
- Market Research and Trend Analysis: Understand public opinion on specific topics or events. Track trends by analyzing sentiment over time.
- Content Optimization for Marketing: Analyze the sentiment of marketing texts to tailor messaging for the target audience. Test and optimize ad content to boost positive responses.
- Automated Text Categorization and Content Analysis: Use sentiment analysis in chatbots to recognize the mood of user queries and respond accordingly. Analyze and categorize large volumes of text data such as news articles or blog posts.
- E-commerce and Customer Reviews: Detect sentiment-rich terms in customer reviews and evaluate trends across different products. Use detailed sentiment data to optimize product descriptions and marketing.
