- (video) https://www.youtube.com/watch?v=o_OZdbCzHUA
- (blog) https://blog.hootsuite.com/social-media-sentiment-analysis-tools/
- (article) https://www.marketingtechnews.net/news/2018/aug/16/how-were-missing-mark-consumer-sentiment-analysis/
- (article) https://towardsdatascience.com/how-to-make-sense-of-social-media-using-machine-learning-8a3db1506d03
- (article) https://itnext.io/sentiment-analysis-concept-analysis-and-applications-8b2c1c6fd77a
The first video above gives a great introduction to sentiment analysis in Python in less than ten minutes. In only fourteen lines of code, the viewer can create a sentiment analyzer for Twitter, which is becoming more and more beneficial to marketers. The first blog post above outlines the benefit of social media analysis and goes over five different tools used in industry. This is a blog on Hootsuite, which is a company focused on getting the most out of social media and telling the same company story across multiple social media apps. The first article above describes the ways in which social media analysis for marketing can be less effective or contradictory to traditional marketing tactics. The second article above is from a distinguished data science website and goes into the details of how to specifically use machine learning to make sense of social media posts. The final article listed above is similar to the last. This article shows examples of social media analysis and also provides a list of tools that can be used to conduct similar studies.
- Example of sentiment analysis dashboard on Tableau, using tweets.
