Let's see how to build a Telegram Bot which checks the emotions in your text with a quantitative approach through sentiment analysis. As already said, the weapon of choice is a Telegram Bot for the APIs ease of use, but any other programmable messenger system will work. A lot of companies offer a good text analysis API (IBM Watson, Google, Api.ai), but this time I decided to use Indico for the ease of use, the nice dashboard and mostly for the node module we can easily integrate in our webtask. We have a running bot, a running webtask which is not getting any message so far () and our AI ready to analyse our emotions and sentiments ().

When someone gives you a good news and you reply with "great" maybe you are not exactly transmitting the happiest of the feelings, but you are happy, really. Lucky us, we live in the age of Artificial Intelligence and writing some code has never been so easy! Let's see how to build a Telegram Bot which checks the emotions in your text with a quantitative approach through sentiment analysis. As already said, the weapon of choice is a Telegram Bot for the APIs ease of use, but any other programmable messenger system will work. What really makes all interesting is the chance to build all this in a serverless architecture: thanks to Webtask.io, which offers an amazing environment, security (powered by Auth0) and serverless endpoints, our server side core will receive the message, send it to the our Text Analysis engine and prettify the answer in order to reply eventually with a nicely formatted response.