The stock market is one of the most sensitive fields, where sentiments of the people can change the trend of the entire market. Actually, there are many factors, affect the movement of the stock market and, the sentiments of the traders are also one of them drive the market.
In present times, stock market investment plays an inevitable role in the finance sector as high stock market value is considered the parameter of high economies. The volatile nature of the stock market has equal chances for earning money and losing money as well. But if the situation can be predicted, investors can make a profit or minimize their losses.
Hence, AI companies are now using sentiment analysis in the stock market to predict the market trend or movement of a particular stock. Social media is one of the best platforms to understand the sentiments of the people trading or investing in the stock market or other financial instruments that are traded on the various exchanges.
What is Sentiment Analysis and How it Works?
Sentiment analysis is basically a process of analyzing the sentiments of people through various platforms like social media and similar websites, where people can freely express their feelings and opinions about anything they think.
Classification of such sentiments can be done at the phrase level, sentence level, and document level. Sentiment analysis uses Natural Language Processing (NLP) to divide the language units in three categories: Negative, Positive and Neutral.
Facebook, Twitter, and Linkedin are the leading social media networking sites, where people share their opinions and express their feelings that show their sentiments. Here people also discuss what they think, whether they are experts in that field or not.
Access to social media platforms through portable devices like smartphones is making easier for the people to post contents and spread their views on various topics. Here sensitive news including fake news or rumors also spreads at a very fast pace.
Such news or information influences the people around the globe and if the news is from the stock market, investors will be also influenced and they will take the decision of buying or selling of stock accordingly. Consequently, that will have a positive or negative impact on the price of the stocks trading on exchanges.
How Sentiments Analysis Work in Stock Prediction?
Sentiment Analysis and the stock market is a well-researched topic. As there are already lots of forces behind the movement of the stock market or particular share of a company. Maybe due to negative sentiment, the stock price goes down or if there are any positive sentiments the stock prices maybe increased.
Since there is no single technique to predict the stock movement accurately, researchers have done lots of experiments to get better results. But due to the universal use of social media websites, they can be considered as important in the prediction of stock movements, as investors share their opinions and thoughts in the media.
When you analyze such social media platforms or microblogging websites using sentiment analysis you can get some idea what people are talking about and what they think about a particular stock. The contents of Social Media such as posts, tweets, photos are analyzed by people of different communities such as politicians, marketers, and analysts, etc., to make the right decision while investing in such markets.
Social Media Contents Based Sentiment Analysis and Prediction System
Social media is playing a key role in sentiment analysis in the stock market. Even over the past few years, the influence of social media sites on everyday life has become so large that even information about large and small incidents or disasters is obtained through social media sites. Due to the influence of social ripple effect of social media sites, diverse studies are in progress to analyse the contents generated online.
Social media content analyses are conducted in diverse methods, and for diverse purposes. Among several contents, especially those texts that are firsthand written by the users contain the most direct and important information. Since contents are created according to the user’s intentions at the time of creation, time also becomes an important factor in sentiment analysis through such contents.
In the current era, the internet user’s popularity has grown fast equivalent to emerging technologies, who actively use online review sites, social networks and personal blogs to express their opinions. This provides an opportunity to know the positive and negative attitudes about people, organizations, places, events, and ideas.
The tools provided by natural language processing and machine learning along with other approaches to work with large volumes of text make it possible to begin extracting sentiments from social media.
Social Media Impact on the Stock Market
As we can see that in the modern world, people make judgments about the world around them when they are living in the society. They show positive and negative attitudes about people, products, places and events. These types of attitudes can be considered as sentiments.
Sentiment analysis is the study of automated techniques for extracting sentiments from written languages. The growth of social media has resulted in an explosion of publicly available, UGC moderation service to control such contents.
While such data and information can potentially be utilized to provide real-time insights into the sentiments of people. Blogs, online forums, comment sections on media sites and social networking sites such as Facebook and Twitter all can be considered as social media that can capture millions of peoples’ views or word of mouth.
Hence, communication and the availability of real-time opinions from people around the world make a revolution in computational linguistics and social network analysis. With the time being, social media is becoming an increasingly more important source of information for anyone including investors trading in the stock markets.
When a piece of news comes in the market, people start talking about it and they give their positive or negative opinions that show their sentiments. Such views can be used by the sentiment analysis experts to predict the movement of the stock market or particular stock of a company.
While on the other hand people are more willing and happy to share the facts about their lives, knowledge, experiences, and thoughts with the entire world through social media more than ever.
Example of Twitter used for Sentiment Analysis in Stock Prediction
The sentiment analysis task is very much field-specific. Tweets are classified as positive, negative and neutral based on the sentiment present. Out of the total tweets are examined by humans and annotated as 1 for Positive, 0 for Neutral and 2 for Negative emotions. For the text classification of nonhuman annotated tweets, a machine learning model is trained whose features are extracted from the human-annotated tweets.
Such data is extracted from twitter and various other similar platforms, and then used a training data set to train the AI model through sentiment analysis algorithms to predict the price of stocks in different scenarios. Except, in extreme or unexpected conditions, most of the time, machine learning or deep learning-based models predict at very high accuracy helping stock market investors to earn money.
They actively participate in events by expressing their opinions and stating their comments that take place in the society. This way of sharing their knowledge and emotions with the society and social media drives the businesses to collect more information about their companies, products and to know how reputed they are among the people and thereby make decisions to go on with their businesses effectively.
To understand the sentiments of people you need an expert. Cogito is providing the sentiment analysis services for the business enterprises, companies and organizations to understand their customers and offer them the most suitable product or services for better response.
Cogito can also help you in developing intelligent sentiment analysis algorithms by providing accurate sentiment analysis dataset through trained professionals. Its analysis system is powered by the latest language processing engine to help you find out the real sentiments and opinions of your customers to understand and offer them the right products or services as per their preferences.