What is Social Sentiment Analysis & Why is it Important for Investors?

Investors are increasingly turning to social metrics to make informed trading decisions. This alternative data set provides many early insights, such as how society views a particular company or industry.

Read on to learn about social sentiment analysis and how it enables investors to outperform the market. We also discuss the best platforms to extract and analyze social metrics in 2023.

Use Cases for Social Sentiment Analysis

Social sentiment analysis had many use cases from various industries and job roles.

Let’s explore some of the most common beneficiaries.

Investors and Traders 

Social sentiment analysis is used widely in the institutional investment space. This includes hedge funds, wealth management firms, and venture capitalists. The reason is simple – these investment houses aim to outperform the market for their clients. The most effective way of doing this is to find trends before they become mainstream.

• For example, consider a hedge fund manager that is exploring the aviation and travel industries.
• They want to assess how society feels about traveling in the midst of the COVID-19 pandemic.
• Through social sentiment analysis, the hedge fund finds that the number of people booking holidays, leaving comments on travel-related pages, and ‘liking’ airline ads is on the rise.
• This highlights that the travel industry is about to witness a major shift
• In turn, the hedge fund might invest in stocks and index funds related to aviation and travel

Now consider the process used by a casual investor. They might wait for traditional media sources to report increased travel numbers. They might also wait for aviation and travel stocks to release their quarterly earnings reports.

Either way, there is a major delay in insights – meaning that the opportunity might have already been lost. In contrast, those conducting social media sentiment analysis can get a first-mover advantage over the broader market. This often means investing in assets at a much more favorable price.

The good news is that social sentiment analysis is no longer reserved just for large investment houses and hedge funds. On the contrary, there are many platforms offering social sentiment indicators at affordable prices. This means that even casual investors can use social sentiment metrics to get an edge on the market.

Researchers and Analysts

Researchers and analysts will also turn to alternative data sources to discover insights and broader trends. And one of the best ways of achieving this is through social sentiment analysis.

• For example, consider a research company that is performing a study on renewable energy.
• The company wants to assess how society views solar panels.
• Through natural language processing, the company can extract relevant data from social media networks, such as Twitter, Facebook, and Reddit.
• The data is then structured to provide insights.
• The analysis shows that while society is largely in favor of home-based solar power, aesthetics remains an issue.
• That is to say, the data highlights that a large part of society doesn’t like the ‘look’ of conventional solar panels on their homes

The research could then be used by investors, solar companies, and other stakeholders to make data-driven decisions.

Marketing Companies 

Social media is one of the best ways for marketing companies to identify sentiment and consumer trends. After all, more than 4.4 billion people use at least one social media network. This is up considerably from 2.07 billion users in 2015. Not only that, but social media networks enable marketers to extract niche insights.

This includes various demographics, such as income, gender, race, age, and location. As such, marketing companies can assess metrics from their preferred target audience.

• For example, consider a healthcare company that wants to launch a new skincare treatment.
• The product is aimed at a young and environmentally-conscious demographic.
• Through social media analysis, the healthcare company can extract metrics from its target audience.
• For instance, those within the 18-30 age group that have previously ‘liked’ or ‘commented’ on environmental-based issues.

Crucially, social sentiment analysis ensures that products and services are targeted to the right demographic. This can reduce costs and increase sales.

How Do Investors Use Social Sentiment Indicators?

Investors use social sentiment indicators to get an edge in the market. Let’s take a much closer look at how the process typically works.

Data Extraction

The initial part of the social sentiment analysis process is to extract data. This usually covers the most popular social networks, including Facebook, Instagram, Twitter, TikTok, and Reddit. As we mentioned above, an estimated 4.4 billion people use social media – often at least once per day.

Now consider how many data points each user leaves on a daily basis. This includes everything from page likes, comments, and posts to status updates and shares. In other words, investors will collect an unparalleled number of metrics from billions of users around the world.

Data Analysis

Once the data has been extracted, it will not offer any value in its current form. Instead, investors need to analyze the data so it yields relatable insights. The most effective way of doing this is through natural language processing. This technology is able to scan vast sums of data and convert it into readable metrics.

For instance, natural language processing tools will evaluate whether Facebook comments toward a company or product are positive or negative. It can also assess whether page likes and shares yield any notable trends. For instance, if a newly launched product receives an increasing number of likes and shares, this would highlight a positive sentiment.

Data Interpretation 

At this stage of the process, the investor has extracted billions of data points from social media and analyzed them through natural language processing. Now that the data has been structured, the investor will look to generate an overall sentiment score. Once again, this requires advanced technologies to streamline the process.

Social sentiment analysis platforms like AltIndex use artificial intelligence and machine learning for this process. These technologies are able to evaluate how the structured data represents broader consumer sentiment. For instance, by comparing the data to industry competitors or previous market trends.

Making Data-Driven Investments 

The final step is to make an investment decision based on the social data collected. The data won’t always yield notable results, but if it does, investors can get an edge on the market.

• For example, suppose the results show that a small-cap biotech company has increasingly positive sentiment on social media.
• This is related to a new drug that treats a critical illness.
• There is growing excitement towards the product, as it has already passed the initial clinical trial stages.
• The data also shows that sentiment is strong on the company’s commitment to ethical practices.
• Overall, the social analysis gives the company a sentiment score of 85/100.

The investor can then use these insights to enter a position in the biotech stock. Considering it has a small-cap valuation, the investor believes there could be plenty of upside in the coming years.

Now consider what happens once the company’s treatment is approved by the U.S. Food and Drug Administration and the European Medicines Agency. The likelihood is that the firm’s stock will appreciate rapidly.

Crucially, the investor will already have entered a position at a much lower stock price. This is because they used social sentiment analysis to yield early insights into the biotech company.

Advantages of Social Media Sentiment Analysis

Now we have explained the basics, we can explore the many benefits of using social media sentiment as an investor.

Find Early Trends

Social sentiment analysis is an effective way to discover and analyze early trends. This is a strategy that has been utilized by hedge funds for many years.

• For example, consider a hedge fund that ran a social sentiment analysis in 2010.
• They wanted to evaluate the streaming service industry. The hedge fund found that an increasing number of people were turning to Netflix and other streaming providers.
• This viewpoint was supported by the number of positive comments and ‘likes’ that streaming services were receiving on Facebook and online forums.
• Conversely, the analysis showed increasing negative sentiment on traditional media sources, like TV and DVDs.

This would have enabled the hedge fund to enter a number of data-driven positions. For example, it might have bought Netflix stock, anticipating rapid demand for streaming in the coming years. It might also have short-sold stocks related to traditional media sources.

Ultimately, social sentiment analysis gives investors a heads-up on early trends, long before they become mainstream.

Discover Small-Cap Gems

One of the most effective ways to find the best small-cap stocks is through sentiment analysis. Small-cap stocks are often new companies that have an unproven business model. This is reflected in their small valuation – which is often below $1 billion. While this increases the risk of investing, small-cap stocks offer a much greater upside than established, blue-chip companies.

But equally, traditional media sources rarely report on small-cap stocks. This makes it difficult for investors to find the next Tesla or Apple. But by using social sentiment indicators, investors can get early insights into undervalued stocks that have a bright future.

For example, consider a small-cap stock that specializes in portable electric vehicle (EV) charging stations. The technology enables EV drivers to charge their cars in the event of an emergency. By running a social sentiment analysis, investors can get early insights into the company.

For instance, the analysis might show that the company is receiving an increasing number of ‘mentions’ on Twitter and Reddit. The analysis uses natural language processing to evaluate whether the mentions are positive or negative. The results show that existing companies are overwhelmingly in favor of the product, value, and overall service.

With this social sentiment data in hand, the investor decides to buy stock in the small-cap company. They have secured a favorable entry price and anticipate long-term growth.

Risk Management Signals

Investors also use social sentiment analysis to assess market risks. This can help protect the investor’s portfolio from a sudden downturn in economic growth.

• For example, suppose the investor currently holds stock in a budget airline.
• They run a social sentiment analysis to assess if any current trends might impact the stock’s value.
• Some notable results are found, specifically about the airline they hold stock in.
• Overall, it appears that there is growing negativity toward the airline.
• Not only in terms of consistently delayed takeoffs but also cancellations.
• What’s more, there is also negativity about the airline’s customer service.
• This includes long waiting times when checking in and an inability to contact the customer support line.

All in all, this data gives the investor a significant time advantage over the broader market. As it appears the airline is having operational issues and increased customer complaints, they decide to sell the airline stock. The investor might also decide to short-sell the stock if they anticipate a prolonged market decline.

Social sentiment analysis can also be used to assess broader industry risks. For example, an analysis might show that fewer people are spending money on discretionary products and services. This highlights that consumers are becoming frugal – a sign that the economy could be retracting. In turn, the investor can reassess their current portfolio to see if it needs to be rebalanced.

Evaluate the Performance of Online-Only Companies

Another benefit of social sentiment analysis is that it provides insights into online-only companies. One of the best data points for this analysis is website analytics. This shows investors how many people are visiting a specific website. The data also highlights how this compares to broader industry trends.

Consider an investor interested in stock trading platforms. Initially, they perform a social sentiment analysis to assess wider trends. For instance, how many people are visiting stock trading platforms and how long they spend on the respective website. Next, the investor breaks the data down to assess whether any platform-specific trends have emerged.

They find that one platform in particular – Interactive Brokers, is trending negatively. That is to say, while the wider industry is booming, the number of people visiting Interactive Brokers is declining. And as the majority of Interactive Brokers’ income derives from online trading commissions, this could highlight sub-part performance.

Rather than waiting for Interactive Brokers to release its quarterly earnings report, the investor can act immediately. This means offloading the stock before the platform reports a decline in revenues and operating income.

Real-Time Insights

Investors with access to real-time insights will also get an advantage over the wider market. This is because there will always be delays when relying on data from traditional media sources. This could be anything from a few minutes to several weeks.

For example, we mentioned above that an investor can leverage website analytics to assess the performance of online-only companies. In contrast, most investors will wait for performance metrics to be released in quarterly reports. This means there is a major time-lag when making investment decisions.

Similarly, consider a technology company that has just launched a brand-new gaming console. The success of the launch will directly impact the value of the stock. By running a social sentiment analysis, investors can get early insights into how the new gaming console is perceived by buyers.

The analysis shows that the gaming console has an overwhelmingly negative sentiment. Not only in terms of gameplay, but high prices and shipping delays. The investor might decide to short-sell the stock before these issues are reported by the mainstream media.

Combine With Other Alternative Data Sources

Social sentiment analysis is just one small segment of the alternative data space. There are many other sources of alternative data available to investors. This includes everything from credit card transactions and real-time flight monitoring to satellite imagery and geolocation tracking.

While social sentiment provides valuable insights, it’s even more powerful when combined with other data sources. For example, suppose an investor runs a social sentiment analysis and finds that there is growing interest in plant-based foods. This is assessed by looking at page ‘likes’ and ‘followers’ of relevant manufacturers and extracting comments and ‘mentions’.

The investor wants to evaluate the validity of their social sentiment findings.

• First, they analyze geo-location data in large US cities. They find that an increasing number of people are visiting plant-based and healthy restaurants.
• Next, they analyze satellite imagery from major plant-based production facilities. They find that the number of daily collections from hauliers is increasing. This indicates that manufacturers are witnessing increased demand for their products.

The investor now has validity in their analysis. They can then enter an investment accordingly, such as buying stocks in plant-based food companies.

Evaluate Daily Active Users Before Official Reports 

Another benefit of sentiment analysis is that it highlights how major social networks are performing. This enables investors to assess the viability of stocks like Meta Platforms and Google. Crucially, the value of social stocks is largely determined by the number of people visiting their platforms. This is usually reported as the number of daily active users, or DAUs.

Suppose that Meta Platforms reports a decline in Facebook’s DAUs over the prior quarter. This will invariably lead to a stock sell-off. This was the case in Q1 2022, when Facebook reported a drop in DAUs – resulting in a 26% stock loss in one day.

There is every possibility that social sentiment analysis could have predicted this decline before Meta Platform’s quarterly report. For example, the analysis might have found lower engagement levels, such as fewer comments, ‘likes’, and shares.

Additionally, website analytics might have confirmed that fewer people were visiting the Facebook website, alongside a lower number of app downloads. This would have alerted the investor to Facebook’s declining DAUs before it released its quarterly earnings.

Social Sentiment Analysis is Affordable  

We mentioned earlier that social sentiment analysis has been leveraged by hedge funds for many years. Crucially, this alternative data source is now available to the masses. Moreover, the best social sentiment tools are affordable.

For example, AltInex plans start from just $29 per month. This provides users with real-time insights from Facebook, Twitter, Reddit, TikTok, YouTube, and Pinterest. This is in addition to Google searches and website traffic. AltIndex tracks thousands of stocks and even the best cryptocurrencies like Bitcoin and Ethereum.

Ultimately, even casual investors can utilize social media indicators to their advantage.

Examples of Social Media Sentiment Analysis: Turning Data Into Investment Insights 

Still wondering how social media sentiment can help investors make smarter decisions?

Let’s unravel some real-world examples to clear the mist.

Example 1: New Product Launch

New product launches made by leading technology companies are extremely important for investors. Success can lead to prolonged stock appreciation. While failures can have the opposite impact.

So let’s suppose that Microsoft has just launched a brand-new smartphone that aims to compete with Apple and Samsung. After the first week of launch, an investor runs a social sentiment analysis to assess overall consumer sentiment.

• Initially, the investor uses natural language processing tools to extract comments from social media.
• Machine learning then sorts through the comments to remove irrelevant data. The relevant comments are then analyzed.
• The data shows that the product launch has been a huge success so far.
• Comments show that the smartphone yields high-quality photos, prolonged battery life, and plenty of storage.
• The comments also suggest that there is positive sentiment on the price of the smartphone.

Although Microsoft isn’t due to release its financial statements for another two months, the investor already has solid insights into its smartphone launch. As such, the investor enters a large position on Microsoft stock.

Example 2: Customer Experiences

Customer experiences will dictate the success or failure of a company – especially those that are consumed-based.

• For instance, consider an e-commerce marketplace that serves customers in the US.
• The company was recently listed on the stock exchange, so an investor runs a social sentiment analysis for some real-time insights.
• Social metrics show that there is increasing negativity toward the e-commerce marketplace.
• There are recurring comments highlighting that deliveries are consistently delayed.
• Comments also show that the website is often slow to load and that many products are sold out.
• The investor also analyzes website analytics and finds that the marketplace is receiving fewer visitors.

The investor determines that there could be a major decline in the value of the firm’s stock. This is likely to happen when the firm next reports its quarterly earnings. So the investor decides to short-sell the company, well in advance of its next financial statement release.

Example 3: Growth Industries 

A growth investor is searching for new trends in the market before they become mainstream. Their first port of call is to analyze social media metrics from Reddit. Considering Reddit has over 100,000 sub-forums and more than 1.7 billion monthly active users, this is a considerable amount of data to work with.

So the investor uses natural language processing and machine learning to extract all comments over the prior three months. After structuring the comments into themes and categories, a trend has emerged. There is growing positivity toward distressed companies that are heavily shorted on Wall Street. Namely, AMC and GameStop.

The data suggests that Reddit forum users are colluding to buy these distressed stocks. Due to the sheer number of users involved, the investor believes this could create a short squeeze. Meaning – Wall Street short positions are liquidated, resulting in a rapid price increase. Therefore, the investor enters a risk-averse position on AMC and GameStop stocks.

Example 4: ESG Investing

An investor specializes in ESG (environmental, social, and governance) stocks. The investor wants to find stocks that have the potential to increase their ESG rating. This can encourage more people to invest – especially fund managers focused on sustainability.

• The investor turns to social media sentiment analysis tools.
• They collect billions of data points from social networks and use machine learning to categorize keywords related to ESG practices.
• The analysis shows that there is an increasingly positive sentiment toward an energy company.
• The firm is allocating vast resources to renewable energy technology, with the aim of reducing its carbon footprint.

This could help the energy firm increase its ESG rating in the near future. The investor decides to buy stock in the firm, in anticipation of updated ratings.

Example 5: Technology Disruptions

Social sentiment analysis is also useful for finding disruptors in the technology sector. For instance, let’s consider an investor that specializes in electric vehicles. They are aware of a new EV manufacturer in Europe that is significantly more cost-effective than Tesla. The firm also claims that it has a longer battery life than Tesla and faster charging times.

• The investor wants to evaluate social sentiment from current drivers of the EV model.
• The investor finds that sentiment is overly positive.
• Comments are increasingly in favor of the cost savings and extended battery life – which supports the manufacturer’s claims.
• The data also shows negative sentiment toward delivery delays, with waiting lists now at 2-3 months.

While the investor acknowledges that supply chain delays are never favorable, this shows that the EV manufacturer is witnessing increased demand. In turn, this negative social metric is viewed as a positive. All in all, the future looks bright for the EV stock. The investor enters an early position on the stock, which still has a small market capitalization.

How are Social Sentiment Scores Generated?

While social sentiment analysis can help investors make better trading decisions, it is important to understand how the data is determined.

After all, each social sentiment provider will have its own methodology and processes. By knowing what to look for, investors can ensure their social sentiment analysis has validity.

Let’s break down the process further, highlighting how social sentiment scores are generated.

Website Crawlers and Bots

Before social sentiment can be determined, investors need to extract the data from their preferred sources. This is usually a combination of social media networks, online forums, and Google searches. This can result in billions of data points being collected. So the use of website crawlers or bots is required.

These technologies scrape text from websites and put it in a centralized database. Importantly, the data collection process must adhere to privacy regulations. This means that individual identities should not be revealed. Instead, the data should be anonymized and aggregated.

Natural Language Processing and Machine Learning

Once the website crawlers and bots have extracted the data, natural language processing and machine learning tools will be used.

• Natural language processing is used to simply split the text into sentiment categories, such as positive, negative, neutral, or irrelevant. This is based on specific words, tone, and emotion.
• Machine learning is then used to clarify the sentiment categories into structured formats. If needed, the data can be broken down further based on demographics. For instance, where users are from or their age group.

Next, the investor will aggregate the sentiment categories into visualizations. For instance, a chart that shows how many people are positive or negative toward solar panel installation.

Artificial Intelligence Scoring

Knowing how many people are positive or negative toward a company, topic, or niche isn’t enough. Instead, investors need to build an overall sentiment score that can be measured and compared.

For instance, suppose an e-commerce marketplace has seen its website visits decline by 20% over the prior month. While at first glance this might seem like a red flag, the overall industry might have declined by 30%.

The most advanced tool to build sentiment scores is artificial intelligence. AltIndex, for example, uses artificial intelligence to build sentiment scores of between 0 and 100.

The closer the sentiment score is to 100, the greater the probability it will perform well in the short-term. And conversely, lower scores could highlight a potential decline.

AltIndex also factors other alternative data sources into its sentiment score. This includes employee satisfaction, job postings, Google searches, and news mentions.

Where Can I Find Social Sentiment Metrics: Top 7 Providers 

Social sentiment data is only as valuable as the platform providing it. Therefore, investors should choose their alternative data sources wisely.

Below, we review the top seven social sentiment analysis platforms for 2023.

1. AltIndex – Overall Best Provider for Social Sentiment Metrics  

We have mentioned AltIndex several times in this guide – and for good reason. We found that AltIndex is the overall best social sentiment provider for retail investors. It offers a cost-effective yet highly valuable database that covers thousands of stocks. This includes small, medium, and large-cap stocks from the NYSE and NASDAQ.

So how does AltIndex work? In a nutshell, AltIndex extracts data from the leading social media websites. This includes Twitter, Facebook, Reddit, and TikTok. It also collects data from other popular platforms, including Google, YouTube, and even 4Chan. AltIndex uses machine learning and natural language processing to categorize the data it collects.

For example, whether the data is positive, negative, or neutral. Moreover, AltIndex uses artificial intelligence to determine sentiment trends. It not only compared sentiment data to previous periods but also industry competitors. To ensure data integrity, AltIndex also extracts information from other alternative data sources.

This includes the number of job postings and how its employees rate the overall company environment. Additionally, AltIndex also analyzes website traffic, app downloads, and financial news articles. Once everything is analyzed and structured, AltIndex gives the respective stock a sentiment score.

The sentiment score ranges from 0 (overly negative) to 100 (overly positive). Investors can then make trading decisions based on its AI scores. AltIndex ranks the best stocks each day from the highest to lowest sentiment. It also sends stock picks to registered users, highlighting which companies could outperform the market.

Moreover, we found that AltIndex is very beginner-friendly. Its dashboard is clutter-free, only highlighting relevant and valuable data. Those wanting to give AltIndex a try can sign up for a free plan. This permits two stock alerts each month but only 20 website visits. For unlimited visits and additional stock picks, plans range from $29 to $99 per month.

2. StockTwits – Real-Time Social Trends on the Hottest Stocks  

StockTwits is the Twitter of the investment community. It is a social network that enables like-minded investors to share trading ideas. Just like Twitter, StockTwits users can post, ‘Like’ and comment. Moreover, each post will contain the ticker symbol for the stock being discussed.

This enables the StockTwits algorithm to build and analyze large datasets. Investors can then extract the data to find out which stocks are trending with retail clients.

In addition, StockTwits also is also popular with cryptocurrency investors. For instance, some investors use StockTwits to find the next cryptocurrency to explode. Although StockTwits offers primary data sources, it doesn’t offer advanced insights. This means that investors will need to use an alternative data provider that can analyze and structure StockTwits trends.

3. Fidelity – Discover Social Sentiment Trends on Over 4,200 Stocks  

Fidelity is one of the largest stock brokers globally. It has developed in-house software that analyzes social sentiment trends. It scans over 4,200 US-listed stocks on a minute-by-minute basis, ensuring that sentiment scores are updated in real-time. The Fidelity methodology is simple – it evaluates whether social sentiment trends are positive or negative.

More specifically, it compares its sentiment scores with previous periods. For example, if sentiment on Nike stock has declined by 20%  since last week, this will be highlighted by Fidelity.

The broker assigns an ‘S-Score’ of between -4.25 and 4.25. Scores between -1 and 1 are considered neutral. While scores above 1 and below -1 are considered positive and negative, respectively. This simple scoring system makes it simple to assess sentiment trends, even as a beginner. Fidelity’s sentiment scoring system is only available to registered users.

4. LikeFolio – Prediction Tool Analyzing Shifts in Consumer Behavior  

LikeFolio is a popular data analytics website aimed at professional investors. It provides investors with daily trends, highlighting shifts in consumer behavior habits. Investors can track specific stocks and receive alerts when trends are discovered. LikeFolio offers social sentiment data on over 10,700 brands.

Its advanced technology can scrape and analyze 2,777 social posts every minute. Although LikeFolio offers valuable insights to stock investors, its plans won’t be suited for those on a budget. For example, access to its dashboard costs a minimum of $25,000 per year. Moreover, those wanting real-time data feeds via an API will need to fork out $40,000.

5. InfoTrie – Combine Social Analytics With Other Alternative Data Sources  

InfoTrie uses artificial intelligence and deep learning algorithms to yield valuable investment insights. The platform specializes in a wide range of alternative data sources, including social sentiment analysis. Its data feeds can scan over 100 million social media data points at any given time.

This covers over 15,000 data categories across more than 70,000 stocks, funds, and cryptocurrencies. InfoTrie also supports forex and commodities. In addition to social analytics, InfoTrie also extracts data from financial news sources.

This is in addition to fundamental research and job market insights. Not only does InfoTrie track data from the US but also the UK, France, Germany, Canada, and Japan. InfoTrie is aimed at institutional investors, so prospective clients need to contact the platform for a bespoke quote.

6. Similarweb – Social Analytics Derived From Website Traffic   

Similarweb specializes in website analytics. It is one of the most accurate providers in this space, tracking millions of websites in real-time. This form of social sentiment analysis provides plenty of insights for investors. For example, investors can find trends on whether a company’s website visits are increasing or decreasing.

This is in addition to the time spent on each website. The investor can then make comparisons with industry competitors. For even greater insights, investors can break analytics down by demographics.

For instance, the data might show that US-based users are spending more time on an e-commerce marketplace. But users from Europe are declining. Other demographics include gender, age, and even device types. Pricing starts at $149/month on a flexible plan. This is reduced to $125/month when purchased annually.

7. RavenPack – Turn Unstructured Data Sets Into Actionable Insights.   

RavenPack will appeal to investors that seek multiple alternative data sets under one roof. It collects and analyzes unstructured data from over 40,000 websites, including the leading social networks. It then packages the data into actionable insights – covering over 80 categories.

This translates into more than 20 sentiment indicators for each stock that it tracks. What’s more, RavenPack also extracts data from financial news websites.

This is in addition to job postings, regulatory filings, and insider transactions. RavenPack also offers insights on key findings, published into easy-to-understand metrics. Like many social sentiment providers, RavenPack is tailored to institutional investors. While it offers a free trial, quotes must be negotiated directly with the platform.

Conclusion

In summary, we have explained the value and importance of social media analysis for investors. Not only in terms of early insights and risk management, but finding new trends and consumer habits.

To get started today, AltIndex offers social sentiment indicators on thousands of stocks. It covers the leading social networks and other alternative data sources. AltIndex also sends stock alerts when new social metrics emerge.

References 

https://umaine.edu/undiscoveredmaine/small-business/resources/marketing-for-small-business/social-media-tools/social-media-statistics-details/

https://hbr.org/2022/04/the-power-of-natural-language-processing

https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained

https://www.fda.gov/

https://www.ema.europa.eu/en

https://www.cnbc.com/2022/02/03/facebook-shares-plummet-22percent-after-reporting-weak-guidance.html

https://www.statista.com/statistics/443332/reddit-monthly-visitors/

FAQs