Machine Learning, Big Data Analytics and Natural Language Processing Techniques with Application to Social Media Analysis for Energy Communities

Today we are in the era of Big Data, and users’ opinions on certain topics are flooding the web. By analysing tweets collected from communities, social media or even messaging systems, it is possible to obtain some interesting results. This phenomenon is important for knowledge workers, who analyse textual content published on the Internet to obtain information that can be used in decision-making. While the content produced on social networks is invaluable for knowledge extraction, the very process of extracting meaningful knowledge is not trivial and involves data and text mining methodologies and techniques that are by no means simple. The following work proposes a batch analysis of information drawn from Tweets by examining texts of news downloaded at different times of the day related to energy communities, using techniques of Sentiment Analysis, Natural Language Processing, Machine Learning and Big Data Analytics.