Sentiment Analysis Service for Reviews, Surveys and Social Media Text
Find out how people feel, at scale. We measure sentiment in reviews, survey comments, support messages and social posts, validate the results against human judgement and report what is driving opinion.
What this service covers
- Polarity classification: positive, negative, neutral
- Lexicon-based methods and machine-learning or transformer models
- Aspect-level sentiment: what people like or dislike about specific features
- Emotion categories where the question calls for them
- Sentiment over time, by segment or by source
- Validation against a manually labelled sample
- Charts, example texts and a plain-language summary
How sentiment analysis works
Simple methods score words from a sentiment lexicon. Machine-learning and transformer models learn patterns from labelled examples and handle context better, for instance recognising that “not good” is negative. No method is perfect: sarcasm, domain jargon and mixed opinions cause errors. For that reason we always check results against a sample that people have labelled and report the accuracy honestly.
Beyond a single score
One overall score hides what matters. Aspect-level analysis separates opinions about price, service, quality or delivery. Trends over time show whether a change helped. Comparing segments shows where sentiment differs. We pair scores with example comments so the numbers are grounded in real language. You can try a quick version yourself with our free sentiment analyzer.
Related methods
To discover what people talk about, combine sentiment with topic modelling. To sort texts into your own categories, see text classification. For survey-specific work, see survey and social media text analysis.
Limits and ethics
We use only data you have the right to analyse, avoid collecting personal data unnecessarily and describe the limits of the method in the report.
How the work runs
- You share the texts and what decisions the results should inform.
- We choose and test the method on a labelled sample.
- We score the full dataset and analyse patterns.
- You receive results, charts and example texts.
What you receive
- Sentiment scores for every text
- Accuracy check against a labelled sample
- Trends and segment comparisons
- Aspect or topic breakdown where relevant
- A summary with recommendations
Frequently asked questions
How accurate is sentiment analysis?
It depends on the text and method. Product reviews are easier than sarcastic social posts. We measure accuracy on your data and report it.
Can you analyse languages other than English?
For several major languages, yes. Tell us the language and we will confirm suitability.
Do you handle emoji and slang?
We can include emoji handling and domain-specific terms to improve accuracy.
Can you analyse my survey comments?
Yes, and we can combine them with the numeric survey results.
What file format do you need?
Excel or CSV with one text per row and any metadata such as date or source.
Is the tool on your site good enough?
The free tool is a quick indication. For decisions, a validated analysis is more reliable.
Related nlp & text analytics services
Topic Modelling
Discover themes in large text collections using LDA, NMF or BERTopic.
Text Classification
Categorise comments, tickets and documents into your own labels.
Survey & Social Media Text Analysis
Themes, sentiment and trends from open-ended answers, posts and reviews.
NLP & Text Analytics Services
See every text analytics service we offer.
Also related: R, Python and MATLAB analysis · Survey data analysis and reporting