The Power of Social Media Analytics: Text Analytics Based on Sentiment Analysis and Word Clouds on R

Abstract

Apparently, word clouds have grown as a clear and appealing illustration or visualization strategy in terms of text. Word clouds are used as a part of various settings as a way to give a diagram by cleansing text throughout those words that come up with most frequently. Generally, this is performed constantly as an unadulterated text outline. In any case, that there is a bigger capability to this basic yet intense visualization worldview in text analytics. In this work, we investigate the adequacy of word clouds for general text analysis errands and also analyze the tweets to find out the sentiment and also discuss the legal aspects of text mining. We used R software to pull twitter data which depends altogether on word cloud as a visualization technique and also with the help of positive and negative words to determine the user sentiment. We indicate how this approach can be viably used to explain text analysis tasks and assess it in a qualitative user research.

Keywords

• Big data
• Text Analytics
• Social Media Analytics
• R
• Sentiment analysis
• Word Cloud
• Twitter Analysis