Ravi Singh
Donald Trump's Sentiment Analyzed Using Tools Developed In Python Programming Language
Donald Trump's Sentiment Analyzed Using Tools Developed In Python Programming Language
Ferro, R. (2018, November 24). Sentiment analysis on Trump's tweets using Python ? Retrieved from https://www.codementor.io/ferrorodolfo/sentiment-analysis-on-trump-s-tweets-using-python-pltbvb4xr
In this article, the author details a comprehensive procedure on how to analyze Trump’s tweets using a programming language called python. According to the author, the sentiment of a user’s tweets can be measured easily using the intensity of negativity and positivity of the posts. In other words, sentiment analysis entails understanding the polarity of different tweets posted on Twitter. Therefore, the author used a small sample of 200 tweets posted by Donald Trump in late November 2018. After subjecting the data to programming evaluation using Python, the author found that about 51% of the tweets sampled had positive sentiment, 27% were neutral, and 22% had a negative sentiment. The author indicated that the accuracy of the results can be enhanced by using a considerably large sample. Although the article seems to have targeted tech-savvy users, it provides an accurate and reliable way to analyze the sentiments of social media leaders.
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