Are you ever curious about what people are saying about your company online? Or what mood the public is in with respect to current events? If so, you should consider using sentiment analysis.
But what is sentiment analysis? Well, in this blog post, we’ll explain what sentiment analysis is and how it works. Stay tuned!
What Is Sentiment Analysis?
Sentiment analysis investigates the polarity of a text or tone of voice when expressing judgment. It’s done by looking at either individual words, parts of speech, or whole sentences that express the attitude of an author towards a topic.
Positive, neutral, and negative aspects are analyzed. It is sometimes used for social media analysis. The process determines public opinion, customer satisfaction, and brand recognition. It also details the best way to reach a target market.
There are three different types of sentiment analysis: lexical analysis, semantic differential analysis, and computational linguistics.
Lexical analysis reviews words individually for their individual sentiment values. This is only possible when a list of words with their sentiment values is available, which varies from system to system. This type of analysis determines if a document has a positive or negative tone overall.
For semantic differential analysis, pairs of words, such as joy/sadness and love/hate, are presented to respondents along with a five-point scale. Usually, the options of very negative, negative, neutral, positive, and very positive are presented.
Respondents indicate their feelings towards the word pair on the five-point scale. The average score is calculated to determine if it’s a positive or negative text.
Computational linguistics is another approach that’s used to determine sentiment. It’s based on psychological research. Mainly, it’s used when a list of words with their polarity isn’t available.
Rather than using a predetermined word list, it uses a machine to find correlations between keywords and sentiment values.
Sentiment analysis algorithm looks at the frequency of different words paired together in a positive or negative way. It gathers context from large textual databases, such as full books or social media posts.
Next, the algorithm analyzes which words combine positively. It also reviews those that pair together negatively. This is done to determine how positive or negative a text is overall.
Lexical analysis has an advantage over semantic differential and computational linguistics. It doesn’t rely on any predetermined word lists.
But out of the three types, computational linguistics is best suited to determine less common words and their sentiment values. It has access to a larger body of textual data.
If you’re interested in learning about helpful sentiment analysis tools, get more sentiment analysis information here.
Understanding Sentiment Analysis
In a world where customers are vocal about businesses, it’s important to understand how sentiment analysis works. It can help improve the way consumers view your company!
So, what is sentiment analysis? It’s a great way to improve rapport with customers.
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