Sentiment Analysis Stock Market in 2024: 3 Data Sources

Figure 1. Time series plot of news sentiment score vs. actual stock price

Making accurate predictions regarding stock prices is challenging as the best time to invest or hold depends on factors like interest rates, inflation, investors’ risk aversion, changes in supply and demand, or quarterly financial reports. 

Even though many factors determine the stock prices in the market, psychological factors such as users’ sentiments regarding policy changes, new investments, or natural disasters also greatly influence how the stock prices change.

Figure 2. Changes in Tesla stock prices in 2022.

For instance, after Elon Musk announced that he bought Twitter, his new investment led to a sharp decline in stock prices for Tesla in the second half of 2022, as the yearly stock down is ~70%.

In this article, we’ll explore how sentiment analysis can be applied to stock market forecasts and the channels you can get sentiment analysis data.

What is stock market sentiment analysis?

Not only do financial forces cause changes in stock prices, but also how the public views the companies in the market, the reputation of the brand among customers, etc. 

Stock market sentiment analysis is one of the web scraping methods for finance that helps gather data to make informed business decisions. Research shows that stock market price movements correlate with public sentiments regarding the companies. 

Moreover, when users’ sentiments are considered in making price forecasts, the accuracy of the prediction models increases by 20%, showing the additional value of customer sentiment in predicting prices.

Thus, sentiment about the company in the media, industry reports, social media reviews, or investors’ opinions can provide great insights into how the prices of stocks change.

Learn more about the use cases of web scraping for finance besides sentiment analysis.

Source: DailyFx

Figure 3. A diagram of how public sentiment affects stock prices in the market

Companies can leverage AI and ML techniques to apply sentiment analysis to understand how the market prices will change over time and take necessary action to buy, sell, or hold their stocks accordingly.

Data labeling has an essential role in sentiment analysis based on categorizing emotional expressions as either negative, positive, or neutral. Labeling data creates a functional, reliable model because the algorithm’s texts, images, or speeches are tagged with meaningful labels and classified into different groups. Thus, data labeling is one of the building blocks of machine learning models, and the models learn these labels that allow for making further classifications. In making predictions regarding stock prices, there are some data sources one may attend to. 

Here are the data sources that may influence stock prices:

1. Employees
2. Partners
3. Customers
4. Suppliers
5. Investors
6. Media
7. Industry analysts/consultants

Where to find data for sentiment analysis in stock market predictions?

1. RSS feeds

Figure 4. An example of a sentiment analysis system that makes stock market predictions using an RSS news feed.

An online file known as RSS news feed allows users to access website material in a standardized format. A positive RSS feed (e.g., FDIs, securing new sales, company financial success, etc.) positively affects the stock market, and the sentiment is reflected in rising stock prices.

NLP-based news feeds help understand the sentiment toward a company and provide insights into the association between sentiments and changes in stock price.

2. Web

A recent study analyzed sentiment toward 87 companies on the websites for seven years. Researchers found a statistically significant relationship between text sentiment and stock price movements. Results indicate that changes in sentiment are the most powerful indicator of market performance. Results show that the market performance in the finance sector is affected the most by the sentiment change.

3. Social Media 

People express their opinion about companies on social media, which gives an idea of their sentiments regarding the companies, which can affect the stock prices. Other than the public, investors also share their opinion on companies, the stock market, or their predictions regarding stock prices. They share their thoughts on sales, prices, the stock market, or financial solutions through different channels. 

There is an association between investors’ sentiment and the market prices in a way that when these opinions involve positive sentiments, stock prices in the market tend to rise. So, examining investor opinions through sentiment analysis methods can provide valuable insights into the stock market’s future.

Twitter is a great alternative data source for analyzing public opinion. A recent study shows that the accuracy of sentiment analysis is almost 90% when the data on Twitter is used regarding 16 companies.

Figure 5. Cathie Wood shares her opinion on Twitter about the sales of companies

Investors express their opinions on purchases, costs, the stock market, or financial solutions. The market prices and investor sentiment are related so that when these views are positive, the market’s stock prices tend to rise. Thus, analyzing investor sentiment using sentiment analysis techniques might offer important clues about the stock market’s future.

You can also check out our data-driven list of sentiment analysis services.

Further reading on sentiment analysis

• Sentiment Analysis Services Benchmarking
• Top Sentiment Analysis Tools
• Sentiment Analysis Datasets
• Top 3 MonkeyLearn Alternatives for Sentiment Analysis

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