Webinar: Sentiment Analysis: Deep Learning, Machine Learning, Lexicon Based?

- Online

“Great movie with a nice story!”

What do you think, did the person like the film or hate it?

Most of the time it’s easy for us to decide whether the message of a text is positive or negative. But what if you wanted to automate the process of understanding the sentiment? For example, if you have a lot of customers leaving comments, or people publishing movie reviews, you will want to discern the sentiment and find out who is posting positive or negative messages.

Sentiment analysis is an important piece of many data analytics use cases. Whether it processes customer feedback, movie reviews, or tweets, sentiment scores often contribute an important piece to describing the whole scenario.

These are just some examples of a long list of use cases for sentiment analysis, which includes social media analysis, 360 degree customer views, customer intelligence, competitive analysis and many more. To avoid doing this manually, we apply sentiment analysis and teach an algorithm to understand text and extract the sentiment using Natural Language Processing.

Join us for our next webinar on text processing on November 27 at 6:00 PM CET where we introduce three techniques for sentiment analysis: lexicon based, classical machine learning and deep learning.