Text Network and Sentiment Analysis. Twitter Mining Project

This project explored a subset of tweets with the help Sentiment Analysis of Text Mining to find out how people concern the idea of “Trump wall” targeting the positive/negative sentiment polarity and averaged emotion distribution through the tweets which were posted between 3 a.m. and 3 p.m. 2019-04-12. Several interesting facts were revealed. People mostly concern such topics as border, prevention, free movement, and other related problems, and compare the Trump wall with apartheid, Berlin wall and so on. The negative bias of the averaged sentiments -7.3% well agrees with that negative tendency -8% reported by press from independent sources. With Emotion Rate of tweets revealed the most joyful tweet “race white” and most fearful tweet “bloody hell how disgusting”. Text network analysis shows three prominent clusters of words which concern the different problems binding with Trump wall. These knowledge may facilitate the solution of the problem.