Maria Ogneva is the Director of Social Media atBiz360, a social media monitoring, measurement and engagement platform. You can follow her on Twitter at@themaria or@biz360, or find her musings on thecompany blog and herpersonal blog.
Automated sentiment analysis has recently been the focus of an intense debate in the blogosphere. How accurate is it? What is the methodology? In what context is it useful for a business or a brand?
Sentiment analysis can be very useful for business if employed correctly. In this article, I will attempt to demystify the process, provide context, and offer some concrete examples of how businesses can utilize it.
What is Automated Sentiment Analysis?
Wikipedia definessentiment analysis as the process that “aims to determine the attitude of a speaker or a writer with respect to some topic.” Automated sentiment analysis is the process of training a computer to identify sentiment within content throughNatural Language Processing (NLP). Various sentiment measurement platforms employ different techniques and statistical methodologies to evaluate sentiment across the web. Some rely 100% on automated sentiment, some employ humans to analyze sentiment, and some use a hybrid system.
Each automated platform has to first be trained to identify sentiment correctly, and methods for doing so vary widely. At Biz360, we usemachine learning to train our system, based on annotations created via Amazon’sMechanical Turk, which basically means that every item in the training data set is annotated by humans first.
Automated sentiment analysis will never be as accurate as human analysis, because it doesn’t account for the subtleties of sarcasm or body language. However, according to our experience with Mechanical Turk, humans only agree 79% of the time. That means even when the raw accuracy of automated sentiment analysis is well below perfect, statistically, it can be thought of as more accurate when compared to human analysis. In other words, automated analysis can be almost as good as human analysis (or, “as good as it gets”).
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