Sentiment analysis in stock market

Stock Market Investment Shot,29th November 2022

Stock Market Investment Shot,29th November 2022

Apart from is the ‘relationship matters’ there is another prime space where sentiments are considered eminent. 

Yes, you guessed it right!


Traders/Investors actions can influence market sentiments who thereby can alter the current trend of the entire market. Market Sentiments becomes paramount because not only do they affect the market but also help to drive the market.

Hence, AI stock advisory companies are now using sentiment analysis in the stock market to predict the market trend or movement of a particular stock. And 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.

How does it work?

Sentiment analysis is basically the process of evaluating 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.

And classification of such sentiments can be done at the phrase level, sentence level, and document level. The sentiment analysis uses Natural Language Processing (NLP) to divide the language units into three categories: Negative, Positive and Neutral.

Sentiment Analysis in Social Media

Facebook, Twitter, and LinkedIn are the leading social media networking sites and also form the main sentiments carrying elements, 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.

And access to social media platforms through portable devices like smartphones is making it easier for people to post the contents and spread their views on various topics. And here sensitive news including fake news or rumours also spread at a very fast pace.

How Sentiments Analysis Used in Stock Market Prediction?

Let us consider an example. If there is a negative sentiment toward a stock, the stock price goes down or vice versa. Although there is no single technique to predict the stock movement accurately, researchers have performed tons of permutations and combinations for better results. Share market advisors have a decent understanding of sentiment analysis based on years of experience.

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.

The nature of contents on Social Media such as posts, tweets, photos is analysed by people of different communities such as politicians, marketers, and analysts, etc, to make the right decision while investing in such markets.

How Real-Time Sentiment Analysis works?

Social media influences our life on an everyday basis. Disasters, Calamities, elections, or even small accidents have a great impact, and obtaining such information through social media on a first-hand basis has just paved the way for unseen opportunities.

Such first-hand written information by the users contains the most direct and important information.

Since content is created according to the user’s intentions, the time of creation also becomes an important factor in social media content based on real-time sentiment analysis in stock prediction.

And 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

Nowadays, people feel the need to convey their consent and judgments in society. They make positive and negative attitudes about people, products, places, and events. These types of attitudes can be considered 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, user-generated content moderation services to control such content. Such raw data can potentially be utilized to provide real-time insights into the sentiments of people.

Hence, communication and the availability of real-time opinions from people around the world make a revolution in computational linguistics and social network analysis.

And with time being, social media is becoming an increasingly more important source of information for anyone including investors trading in the stock markets.Technology-driven share market advisors are making use of it and helping thousands of investors start their financial journey.

While on the other hand people are more willing and happier to share the facts about their lives, knowledge, experiences, and thoughts with the entire world through social media more than before any platform of media sources.

Twitter Sentiment Analysis for Predictions

The sentiment analysis task is very much field-specific. Tweets are classified as positive, negative, and neutral based on the sentiment present.

Tweets are examined by humans and annotated as 1 for Positive, 0 for Neutral, and 2 for Negative emotions. For the 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 as 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 investors and stock advisory companies earn money.

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