Sentiment Analyzer - Score Text as Positive or Negative with a Word List

Use the free Sentiment Analyzer below: your data never leaves your browser — all work happens on your device, and nothing is uploaded to any server.

A quick read on the mood of a text

Is this review happy or angry? Is this batch of feedback mostly pleased or mostly frustrated? Reading every message to answer that question takes time, and gut feeling about a whole pile of text is unreliable. A sentiment tool gives you a fast, repeatable first answer: a score, a label, and the exact words behind both, so you can check the reasoning instead of trusting a black box.

This tool is lexicon-based, and that label matters. It compares your words against a fixed built-in list of positive words such as love, great and excellent, and negative words such as hate, terrible and awful. Every match adds or subtracts one point. The final score is the difference, and the label follows the sign: positive, negative or neutral. No machine learning model is involved, no text is sent to an AI service, and the word lists are the same every time you run it.

How to read the result

The headline shows the label and the score, for example Positive (+6). Below it you get three counts: how many positive words were found, how many negative words, and how many scored words in total. Then the tool lists the actual matched words on both sides, so you can see at once whether the score rests on a few strong words or on many mild ones. A score of +2 from two words is weaker evidence than +2 from ten words against eight, and the detail panel lets you tell the difference.

What a word list cannot understand

Honesty about the limits is part of using this tool well. A word list does not understand negation: “not happy” scores as positive because it sees “happy” and misses the “not”. It does not understand irony, so “great, another delay” scores as praise. It does not understand context, so “killer feature” counts as violent and “sick beat” counts as ill. Domain words are missed too: in a medical text “positive” can be bad news, and in finance “bearish” has no place on a general list. Treat the score as a signal to investigate, never as a verdict.

Getting useful results anyway

The tool is most reliable on straightforward, emotional text: product reviews, short survey answers, social comments and customer messages where people say plainly what they feel. It is least reliable on long formal writing, sarcasm-heavy text and texts that mix praise and complaint in equal measure. For a batch of messages, run each one separately and look at the distribution of labels rather than averaging scores into a single number, since an average can hide a split audience. And always read a sample of the texts behind an extreme score before acting on it.

Practical uses

Small shop owners scan a week’s reviews in minutes. Community managers spot a sudden run of negative comments. Students demonstrate how sentiment analysis works before moving on to more complex methods. Writers test whether a draft’s tone lands as intended. In every case the value is speed plus transparency: you see the score and the words that made it, and you stay in charge of the judgement.

A worked example

Consider the sentence “I love the design but hate the battery life”. The tool finds one positive word, love, and one negative word, hate, giving a score of zero and a neutral label. That is technically correct by the counting rule and clearly incomplete as a judgement, since the sentence mixes praise and complaint about different things. The lesson is to use the tool at the level where the text is uniform in feeling: split a mixed review into its sentences or its topics first, score each part, and then describe the mix in your own words. The tool counts; you interpret.

Privacy note

Everything runs locally in your browser. Feedback, reviews and messages you paste are never uploaded to a server or fed into any model, which is exactly what you want when the text belongs to customers or contains personal feelings. Paste, read the score, copy what you need, and nothing remains behind.

Sentiment Analyzer – Score Text as Positive or Negative with a Word List