With multiple social media platforms available to brands for marketing, campaigning has become so much easier for them today. The best part about online marketing campaigns being run on social media is that audience reactions are instant. Recent technological advances and the use of algorithms for a deep understanding of hidden texts have improved drastically. Many advanced artificial learning techniques are being used as they are an effective tool for conducting in-depth research. One such tool being used to evaluate audience reactions is sentiment analysis. Here is a brief guide about what sentiment analysis is and how it has proved to be beneficial.
What is Sentiment Analysis?
Sentiment analysis, also widely known as opinion mining, is an often misinterpreted term. Sentiment analysis is the most popular text classification tool. This tool is adopted for the contextual mining of text that helps identify and extract subjective information through monitoring online conversations. It is used for the analysis of an incoming message and helps determine whether the underlying sentiment of the message is positive, negative or neutral.
This is an extremely great tool to comprehend the emotional tone of the audience concealed in a string of words that offers a profound understanding of their attitudes, opinions and emotions.
Why is Sentiment Analysis Important?
More than half of the world’s data is not only unstructured but also unorganized. Most of this data is gathered through mails, chatting websites, social media platforms, articles, documents and surveys. It can be really tough, time and money-consuming to assess, comprehend and sort through this data. It is nearly impossible to do this manually.
This is where the sentiment analysis system comes in. It allows organizations to make sense of all this unstructured data through the automation of data processing rather than opting for manual data processing. Sentiment Analysis has helped businesses become more efficient and cost-effective. Here’s how sentiment analysis is benefiting organizations.
Scalability
According to Goascribe, it is nearly impossible to sort through the millions of tweets, customer reviews or customer support conversations manually. There will be way too much data to process manually. Sentiment analysis allows the processing of huge data sums in an efficient and inexpensive manner.
Real-Time Analysis
Sentiment analysis provides instant feedback. It allows for the identification of critical and important information, especially during certain situations that require instant feedback. Situations like a PR crisis require immediate damage control. Using a sentiment analysis system can aid you in tackling such issues immediately.
Consistent Criteria
Judging situations is a subjective task. Humans don’t always follow through on the criteria when assessing the sentiment of a certain piece of text. People might only agree about 60 percent of the time when evaluating a piece of text as they are significantly influenced by their own experiences and thoughts. However, sentiment analysis allows businesses to apply the same criteria to all their data, reducing errors and improving data consistency.
The Bottom Line
Wondering about how to improve sentiment analysis? Well, just like any other automated process, sentiment analysis is also prone to errors. Therefore, it requires a human eye to ensure that it runs efficiently.