Sentiment Analysis for better Stock Market prediction

Published by FirstAlign

Artificial Intelligence (AI)  is the ability of machines to learn from data and provide human-like insights. Today AI is a way of life, from voice assistants like SIRI to more complex applications like self-driving cars. AI will have a wide adoption in every industry and is likely to be one of the next significant technological shifts. 

Image by Ahmad Ardity from Pixabay

Predictive analytics is the process of analysis of historical data to determine outcomes or events. It can give great insights that can accelerate a company.AI algorithms can process complex data to identify patterns and predict possible outcomes. 

The best AI systems in the world are efficient prediction machines.

Stock price prediction

Does investing in the stock market scare you? You are not alone! Investing in the stock market carries risk. You need to understand the tricks of the game to win at the stock markets. A successful stock price prediction is a smart trick to have up your sleeve. 

In the stock market, technical analytics use numerous patterns such as head and shoulders or cup saucer alongside other technologies to determine the future price. 

These different methods have their own merits and disadvantages, but are not very reliable. With the advent of machine learning, stock market prediction has moved into the technological realm.

What is sentiment analysis?

Sentiment analysis is the process of identifying negative or positive sentiment in text. It is often used to analyze textual data to detect emotions. Sentiment analysis is an essential tool to monitor and understand the mood of customers.

Knowing how the financial market will behave in the stock market is an added advantage and can prevent heavy losses. It is a market sentiment that moves prices in the short term. Market sentiment is an aggregation of opinions, views, or outlook at any point in time. 

AI for Sentiment Analysis

Social media is a powerhouse of data. Facebook, Twitter, Instagram are some social media platforms where people express their opinions. Undoubtedly, these platforms are influencing a great deal of the world today. 

On these platforms, news travels like fire. It essentially makes the stock market even more volatile. AI can use these large volumes of social media data to make meaning out of it. Using natural language processing (NLP) for sentiment analysis, social media data is processed into three categories: positive, negative, and neutral. These insights can help in stock price prediction. 

Oscar Javier Herandez, a published Ph.D. student at the University of British Columbia, carried out a consulting project for ApiThinking. The project’s objective was to understand the role of Twitter sentiments on a company’s stock returns.

The project’s main finding was a small amount of stock return sensitivity to Twitter data. Though it was not clear what that relation is ahead of time. The sentiment correlation may change depending on the type of news and how people responded to it. Hence it was essential to track it over time.

It indicates that how people respond to news on Twitter and its correlation to stock will give us some predictive power than others.

Summing Up

The highly volatile and risk-oriented stock market is innovating with better analytics using AI. Stock price prediction can make or break for investors.  Sentiment analysis can help predict a stock price by understanding people’s sentiments at a given time. The best place to look for opinions is social media platforms.

Using AI algorithms, we can process vast volumes of social media data to gather insights. These meaningful insights help technical analysts of the stock market to predict stock prices. 

We can make the approach more efficient by collecting data from different sources such as social media platforms, news etc., to improve the sentiment model. As AI evolves with the latest advancements, we can expect exciting opportunities in trading. 

[Featured photo by Adam Nowakowski on Unsplash]


Published by FirstAlign

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