Sentiment Analysis in Everyday LifeWith technology’s increasing capabilities, sentiment analysis is becoming a more utilized tool for businesses. Social media monitoring tools use it to give their users insights about how the public feels in regard to their business, products, or topics of interest. It’s widely used by email services to keep spam out of your inbox and by review websites to recommend new content like films or TV shows. However, it has been used in more murky circumstances. Facebook, for example, came under fire when it was discovered they were using sentiment analysis to see if they could manipulate people’s emotions by altering their algorithms to inject negative or positive posts more frequently into their users’ news feeds. By using this process of “emotional contagion,” they found that they could decisively influence their users’ emotional output by flooding their news feeds with positive or negative posts. The big problem is that Facebook never informed its users that they were part of an experiment and may have caused emotional distress to them in some cases. Clearly we can see how this use of sentiment analysis can be problematically unethical. But our main interest today lies in how sentiment analysis is used with social media monitoring tools.
How is Sentiment Analysis Performed?There are three machine learning classification algorithms that are predominantly used for sentiment analysis in social media listening:
- Support Vector Machines (SVMs)
- Decision Trees