How can our Sentiment Analysis help you become more productive?
If you find yourself in the need to get a quick idea (e.g. public opinion) based on a product/person/event/trends from big data, such as tweets, Instagram posts, discussions on different social media, or newspaper articles, this task will end up being particularly tricky. Indeed, you will find yourself having to manually analyze all the data and, in turn, you will encounter scope problems.
The Sentiment analysis module is an opinion mining system based on natural language processing and machine learning that aims at quantifying the sentiment wrapped in a piece of text. This system takes a batch of sentences, processes it and assigns a sentiment score to each sentence, ranging from -1 (very negative) to +1 (very positive).
State of the art regression model uses the latest advances in natural language processing and deep learning to analyze the sentiment behind text data. Batch processing and parallelization allows you to parse hundreds of sentences in a matter of seconds.
What are the perks?
Listed below are a some of the assets that our Sentiment Analysis provides:
- Extremely simple to use: select your source of text. Sentences can come from a parsed document or from our Twitter request API.
- No code needed: once your app is set up in the studio, everyone can use it. No need to be a data expert to tune the system to your needs.
- Applicable to literally any piece of text: our module tackles sentences coming from very broad and different sources.
- Accelerate analysts’ work: our sentiment score can be used by analysts and can be fed to other numerical analysis modules.
Where we perform particularly well
Among the key elements that make us stand out is the ease of use, the accuracy and the speed at which results are provided.