Social media has gradually become an integral part of our lives. It is the place where a majority of people feel confident to express their feelings and opinions. Thoughts are shared on social media day and night by billions of people who use these platforms. It is the commonplace to hang out with friends and family, especially after the pandemic has risen to a level where physically meeting people has become a danger to life. Naturally, businesses have shifted their attention to social media to proliferate the market with their products and services. But unlike other data, the sentiment of the users towards a brand cannot be easily measured. The data available on people’s opinions about a brand is vast, diverse and scattered across the internet. Thanks to sentiment analysis, analysts across the globe are able to track and report the attitude of people towards a particular product or brand. So we shall try to understand what is the fundamental purpose of Sentiment Analysis on social media.
What is Sentiment Analysis?
Also called opinion mining, Sentiment analysis is contextual mining of text which extracts and identifies subjective information from the target material. Basically, it is the process of figuring out the emotional tone behind a series of texts or words written online in order to gain a better understanding of the emotions, opinions and attitudes expressed by the writer. Although it has vast uses, it is primarily used by large corporates to help a business to understand the social sentiment of their product, service and brand while monitoring online conversations.
What is Social Media Sentiment Analysis?
Social media Sentiment analysis is the use of natural language processing (NLP) on social media platforms to analyze social conversations and feedbacks to determine the deeper context as they apply to a topic, brand or theme. It is a form of social listening that can improve the bottom line of your brand. It shows how users feel about a particular brand and also compares to other competitors.
What is NLP?
NLP is a vast field that caters to other tasks than sentiment analysis alone. It is a process that includes various studies like artificial intelligence, computer science, and linguistics. As previously mentioned, billions of people share what they are thinking about entities. Making machines understand the natural language is vital so that they would be able to perform various functions like translations and answering queries. Natural language processing is used to track keyword searches and check the spellings among other things. An example would be finding the synonyms to words you require. Apple Siri, Amazon Alexa, Google Translate, etc are some of the applications using NLP for machine learning processes.
Sentiment Analysis purpose on Social Media
Sentiment analysis is pivotal in social media monitoring because it allows us to gain an overview or sentiment of a wider public opinion behind certain topics. Social media monitoring tools with real-time monitoring capabilities make that process quicker and more effective than ever before.
The usage of sentiment analysis on social media is broad and powerful. Organisations across the world are widely adopting the ability to extract insights from social data to their advantage. Lifts in the stock market have been shown to correlate with shifts in people’s sentiment on social media.
Ahead of the 2012 presidential election, The Obama administration used sentiment analysis to measure public opinion to campaign messages and policy announcements. They were more effectively able to strategise and plan for the future by being able to quickly see the sentiment behind everything from news articles to forum posts.
Sentiment analysis can also be an essential part of your customer service approach and market research.
You see what people think of the product and services offered by your competitors along with how they feel about your own product and services. If the online sentiment towards a newly launched line of products of a famous brand is generally negative, then it will help the brand to make necessary changes including modifying the cause for the declining sentiment or even halting production altogether before the damage gets out of hand.
Social media influencers are paid big bucks to opine about products after using them on-screen to come forth as honest feedback rather than the conventional methods of scripted advertisements. They are sent free samples to try out and feature them on their social media like Instagram, Youtube, Facebook and others.
Tone & Contextual understanding
Sentiment analysis, however advanced, is not a perfect science at all since the human language is complex and tone specific. Programming a machine to perfectly analyse the various slangs, grammatical nuances, cultural variations, abbreviations and misspellings that happen in online mentions is a difficult process. Teaching a machine to understand how context and tone can alter the meaning of a sentence is even more difficult. When it comes to interpreting the tone of a piece of writing, humans are fairly intuitive.
For example take the following quip made online: “My amazon package is now showing missing. Just great!”
Anybody who reads this would be able to quickly interpret that the person was being sarcastic and is upset about the delay in the package delivery. We can easily identify the sentiment as negative, by applying contextual understanding to this sentence. However to a machine without contextual understanding will see the words “just great” and categorise the sentiment as positive, which is far from the truth.
The field of natural language and machine learning techniques processing both have their role to play in the future of effective utilization of sentiment analysis. There is still a long way to go achieve the desired perfection to fully automate the process of sentiment analysis. The age of getting meaningful insights from social media data to make necessary modifications to a brand is already in place with the current advancement in technology. Once perfected it will be the game-changer that will revolutionize the online eCommerce industry through social media.
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