What is Social Sentiment Analysis & Why is it Important to Finance?

Social media provides an unparalleled amount of data for investors – especially when it comes to trends and consumer sentiment. After all, an estimated 4.8 billion people use at least one social media network.

In this guide, we explain how social sentiment analysis allows investors to make smart decisions. We also explore where to find social sentiment data and how best to use it when investing.

Who Uses Social Media Sentiment Analysis?

Now that we have explained the basics of how social media sentiment works, let’s explore who uses this analysis method. 

Financial Institutions

Financial institutions, including fund managers and hedge funds – invest significant amounts of money into social media analysis. The reason for this is simple; social media insights provide valuable data on broader consumer trends.

For example, suppose that Apple has recently launched its latest iPhone model. After a week of its launch, sales have been phenomenal. However, a growing trend on social media has emerged – consumers are complaining about the model’s poor battery life. A few days have passed and the same complaints are being shared on Twitter, Facebook, and other social networks.

A fund manager uses this social data to enter a short-selling position on Apple. Once traditional media sources pick up on the iPhone’s defect, the issue becomes mainstream. This results in an Apple stock price decline.

This is just one example of how investors can turn social sentiment analysis into smart investment decisions.

Brand Reputation and Customer Experience Departments

Brand reputation is a crucial component of any company – especially in the digital age. This is why many companies now have specific departments solely dedicated to evaluating public perceptions.

Social media analysis is one of the most effective ways of achieving this goal. It wouldn’t be feasible for multinational companies to manually review social media feedback. Instead, companies use machine learning and natural language processing models.

These technologies scrape data from billions of data points and present the results as simple yet valuable insights.

For instance, consider an electric vehicle company like Tesla. After performing social sentiment analysis, they find that drivers have concerns about the safety of its autopilot feature.

A smart marketing move might be for Tesla to release a press statement. It could explain to drivers how its autopilot feature is safe, alongside some stats on safety records.

Marketing Agencies

Marketing agencies are another beneficiary of social sentiment analysis. After all, companies want to ensure that their products and services are being marketed to the right audiences.

Not only that, but social sentiment analysis also enables marketing agencies to evaluate existing ad campaigns. For instance, suppose an apparel company is in the midst of a social media ad campaign for a new clothing line.

The company can use social sentiment metrics to evaluate how consumers have responded to the ad. For instance, the number of clicks, likes, shares, and engagement. If the overall sentiment isn’t positive, the firm might decide to pull the ad.

Customer Service Agents

Customer service agents will regularly monitor social media for any questions or concerns that need to be answered. This protects the brand’s identity and provides an overall positive customer experience.

For example, suppose a large technology company finds increased mentions on Twitter about delayed shipments. The customer service agent can report this to the relevant department to find a real-time update.

The customer service agent can then reply to these concerns on social media. This will bode well in the long run for the company, especially when it comes to brand sentiment.

Political Analysts and Polling Companies

Political analysts regularly use social sentiment analysis to evaluate public opinion. Not only in terms of upcoming election predictions but also key concerns from the general electorate.

Social media analysis is also used by polling companies to provide estimates on election results.

How Do Social Sentiment Indicators Work in Finance?

While social sentiment serves many different industries, it is increasingly becoming mainstream in the finance space.  

Below, we explain how the process works when using social sentiment indicators to make investment decisions.

Data Collection

The first part of the process requires financial institutions to collect data from social media networks. This often includes Facebook, Twitter, and Instagram, as well as Reddit and Tik Tok.

Some of the data points that will be collected include page follows, likes, shares, and mentions. Community engagement will also be extracted, such as comments and status updates.

Data Analysis

Once the data has been collected from social media networks, the financial institution will analyze it. This will often consist of billions of data points, so emerging technologies are required.

For example, the financial institution might have bespoke language processing and machine learning algorithms. This will separate the good data from the bad, by identifying positive and negative metrics.

Data Aggregation 

After the data has been collected and analyzed, it will then need to be aggregated. This means categorizing the data into identifiable categories. In doing so, this enables the financial institution to interpret the data.

The aggregation process also enables the data to be broken down by demographics. This might include age, gender, and income band.

Market Correlation 

At this stage, the financial institution has extracted billions of data points from social media, which is now packaged in an aggregated format. This enables the financial institution to look for a correlation between social media sentiment and asset price performance.

For example, suppose the collected data shows that over the prior week, consumer sentiment on Tesla has declined considerably. Based on an AI-scoring metric, sentiment is down 20%. Over the same timeframe, Tesla stock has dropped by 8%.

The financial institution could then hone in on this finding. For instance, they could look for other data sets that show similar findings, in terms of consumer sentiment. This then gives the financial institution an edge in the market.

Oftentimes, social sentiment moves at a faster pace than traditional media sources. This means that social sentiment analysis gives investors a time advantage.

Automated Signals 

Over time, the use of natural language processing, machine learning, and social sentiment analysis can yield valuable results for financial institutions.

This is because as more and more data is collected, analyzed, and interpreted – more accurate correlations will be discovered. This enables investors to automate the analysis process through signals.

For instance, if an identified market correlation has been discovered by the algorithm, this will send a signal in real-time. The investor can then decide whether to buy or sell the asset, based on the identified trend.

Benefits of Social Media Sentiment Analysis for Investors

In this section, we explore the key benefits of using social sentiment analysis to make smart investment choices. 

Real-Time Consumer Insights

Social sentiment analysis offers real-time insights from billions of consumers. This enables investors to find trends and metrics before the price of a stock responds.

For example, suppose Meta Platforms releases a demo video of its soon-to-be-launched augmented reality headset. After extracting relevant data from social media, data suggests that consumer feedback is largely underwhelming.

The key issues presented by the data include a high price point and lack of identifiable use cases.

With this information at hand, an investor might decide to sell their Meta Platforms position. Alternatively, they might also decide to short-sell Meta Platforms stock to profit from a potential price decline.

Effective Risk Management   

Investors are prone to panic sell on the back of a negative news story or falling stock price. But this often means that the investor has exited their position too late, with a big percentage loss on the horizon.

By using social sentiment analysis, investors can implement a more effective risk management strategy. For example, consider a pharmaceutical company that has just completed an unsuccessful clinical trial. Word gets around on social media that the clinical trial has resulted in critical health issues for many of its participants.

As the news is yet to surface on mainstream media, the investor has a chance to offload their position in the pharmaceutical company. This is long before the broader markets begin to panic sell.

Public Figures and Influencers    

Another benefit of social sentiment analysis is that investors can extract insights from public figures and influencers. Once extracted and analyzed, investors can look for correlations between posts and asset price movements.

For example, in 2021, the price of Dogecoin witnessed a considerable increase when Elon Musk tweeted about the meme coin. This occurred on several occasions. Social media signals enable investors to receive information on relevant tweets in real-time.

Similarly, analyzing the posts and tweets of social media influencers can also yield similar results. For example, suppose an influencer with over 10 million followers regularly posts positive reviews about newly launched technology products. The data shows that this often results in a short-term price increase of the respective stock.

Investors can then build this predictive model into their data sets, enabling them to trade futures posts in real-time.

Broader Industry Trends

Social sentiment analysis provides real-time insights into broader industry trends.

For instance, suppose an investor is researching the solar energy market. They want to gauge overall consumer sentiment on solar panels in the consumer market, so they utilize social sentiment indicators.

The data suggest that there is growing positivity surrounding solar panels. In particular, data shows that government subsidies and energy bill savings are proving popular.

The investor might then decide to invest in an ETF that tracks social energy stocks.

Contrarian Positions

Social media sentiment is also useful for taking contrarian stock positions.

For example, suppose there is growing negative sentiment on a video console manufacturer because of delayed shipments. In turn, the manufacturer’s stock price declines.

However, the investor takes a contrarian approach, as the overall fundamentals of the video console company are strong. As such, the investors buy stock in the company while prices are cheap.

Once supply chain constraints are resolved, the price of stock rebounds.

Economic Trends

One of the best features of social sentiment analysis is that data can be broken down by specific demographics. This enables investors to assess economic trends in individual countries.

For example, suppose that the extracted data shows that non-essential spending is trending upward in Australia. This includes high-end products, such as cars and electronics.

The data highlights that overall consumer sentiment is positive in Australia. In turn, the investor can explore suitable investments to gain exposure to this growth – such as an index fund.

Social Media Sentiment Analysis Examples

To gain a clearer understanding of how social media sentiment analysis works, let’s look at some real-world examples. 

Social Media Mentions

Social media mentions offer great insights into stocks and the best crypto to invest in right now. This metric refers to the number of times the asset is mentioned on a particular social media network, over a set period of time. The investor would then need to compare the results to historical data. If a trend appears, there might be a good reason for this.

• For example, AltIndex data shows that over the prior month, the Bank of America received an average of 570 Twitter mentions each day.
• But in the prior 24 hours, the Bank of America was mentioned 5,568 times. This represents a notable increase of almost 10x.
• In contrast, some of its main competitors, such as Citigroup, JPMorgan Chaser, and U.S Bancorp, saw their Twitter mentions decline.

The investor uses social media sentiment analysis tools to look for trends. They find that there is increasing negative sentiment on the Bank of America for increasing its personal account fees.

The investor decides to short-sell Bank of America stock, anticipating a short-term decline.

New Cryptocurrency Launches 

Investors can also use social sentiment analysis to find the next crypto to explode.

For example, some of the best meme coins in recent months have generated gains of several thousand percentage points. Much of this is because of hype and FOMO (fear of missing out) generated on social media.

By using social analysis tools, investors can find cryptocurrencies that are trending.

Real-Time Alternative Data 

There is often a sizable lag between real-world events occurring and the mainstream media reporting it. Social sentiment indicators can remove this lag through real-time searches.

• For instance, suppose a corn trader is looking for localized information from Ukraine.
• They want to assess whether or not Ukraine’s major corn supply route is operational.
• Through social media tools, the investor can extract data from people on the ground.
• If there is increased tension in the supply chain region, this could hold shipments up.
• In turn, the price of corn could see an immediate increase.

Investors using social media tools for real-time data can get a first-mover advantage.

Active Users and Subscription Numbers 

Some companies rely heavily on the number of people that visit their platform. This is especially the case for social media networks.

• For example, the BBC reported that in February 2022, Meta Platforms lost $230 billion from its market capitalization in one day – the largest in Wall Street’s history.
• The reason? The number of daily active users on Facebook declined for the first time since it went public in 2012.

There is every chance that this could have been predicted through advanced social sentiment tools.

For instance, technologies like artificial intelligence and robotic process automation could have looked at the number of posts, likes, comments, and other metrics over the period. It could have then compared this to previous quarters and determined a potential decline in active users.

An investor would have then been able to short-sell Meta Platforms stock long before it announced the news.

Foot Traffic and Consumer Ratings

Another example of how social sentiment analysis can aid investors is foot traffic data.

For instance, social networks like Facebook enable people to ‘check-in’ to places they visit. Check-ins can also occur when somebody uses a public WiFi service. Either way, this provides investors with valuable data.

Suppose the investor is researching a US-based restaurant chain. The investor notices that an increasing number of users are visiting the chain – and spending longer periods of time there. The investor also notices that customer ratings are increasingly positive.

Taking all of this information into account, the investor decides to buy stock in the company.

How is Social Sentiment Determined?

Social sentiment looks at the broader picture. In other words, how does the vast majority of society feel about a particular brand, product, or trend? The only way to make a legitimate analysis is to extract significant amounts of data, which then needs to be analyzed, aggregated, and filtered.

As we mentioned earlier, social sentiment analysis looks at billions of data points. It looks at the most relevant metrics, such as the number of followers, mentions, and likes specific pages or topics receive. The analysis process also uses natural language processing and robotic process automation to convert comments and posts into useful data.

Once all of the data has been analyzed, the aggregation process begins. This means categorizing the data based on the investor’s needs. For instance, it might separate positive and negative sentiment into two data sets. The data can then be broken down by demographics. For example, while younger people might like a new product launch, this might not be the case with the older generation.

Ultimately, social media sentiment isn’t always a reliable indicator. For example, while negative sentiment on a company might be growing, its stock price could still be on an upward trajectory. This is just the nature of the financial markets. Sure, social metrics offer insights into trends, but other factors need to be considered too. This includes the fundamentals of the company – such as its revenue, profit margins, and debt levels.

Social Sentiment Analysis Providers

Performing social sentiment analysis without a specialist platform is beyond the realms of possibility. After all, data needs to be extracted and analyzed from billions of metrics.

Below, we discuss some of the best social sentiment analysis platforms for 2024.

1. AltIndex – Best Social Sentiment Analysis Provider for Beginners 

One of the best alternative data providers for performing social sentiment analysis is AltIndex – especially for beginners. AltIndex offers a user-friendly dashboard that is simple to use. It supports thousands of stocks from the US markets, offering plenty of options for investors. Most importantly, AltIndex offers a significant amount of social data that is updated every day. The data is analyzed and aggregated behind the scenes, so users simply see the trends that have been identified. 

For instance, for each supported stock, users can review the number of social media followers – and whether this is up or down from previous periods. Many social networks are supported, including Twitter, YouTube, Facebook, Instagram, Pinterest, and Reddit. AltIndex also extracts mentions from these platforms, not to mention overall user engagement. We like that this leading AI stock picker aggregates its social sentiment data and provides a score out of 100. 

The closer to 100, the higher the sentiment for the respective stock. The scoring methodology also uses artificial intelligence, providing users with advanced prediction models. In addition to social media metrics, AltIndex also looks at internet trends. For example, how many times the stock is being mentioned in traditional media sources, like financial news websites. It also analyzes Google search figures and app downloads, if applicable. 

AltIndex will also appeal to cryptocurrency investors. While it supports a limited number of coins, it covers the most popular ones. This includes Bitcoin, Ethereum, Litecoin, and Dogecoin. We like that AltIndex is free to use, but this limits the number of stock/crypto alerts to two. To increase this 10 or 50 alerts, users will need to pay $29 or $99 per month, respectively.

2. Social Sentiment by Fidelity – In-House Social Sentiment Scores From Twitter Data 

Fidelity is one of the largest investment brokerages globally. The platform recently launched its Social Sentiment feature. This analyzes data from Twitter on a 24/7 basis to find sentiment insights. Fidelity uses a three-step process to obtain its data.

First, it extracts the data from Twitter. Second, Fidelity removes spam and non-relevant data. Finally, the relevant data calculates an overall S-Score. This runs from -3 to +3. The closer the +3, the more positive consumer sentiment is on the stock.

The Social Sentiment feature is available to all registered users. There is no additional charge, but users will need to have a verified account. Fidelity offers 0% commission trades on US-listed stocks, so the platform is ideal for acting on its social signals.

3. StockTwits – Investment-Based Social Network With Real-Time Sentiment Trends  

StockTwits is a social network that specializes in stocks. It operates like other social platforms, enabling users to share and like posts, as well as leave comments. However, all discussions are investment-related. This makes it ideal for social sentiment analysis. 

For example, the platform is backed by an algorithm that analyzes posts, known as ‘twits’. The algorithm will determine whether a specific stock has a positive, negative, or neutral sentiment. This is based on user engagement on the StockTwits website. We also like that users can search for their preferred stocks. 

This will then display a sentiment score from -4.5 to +4.5. The closer to +4.5, the more positive the sentiment. Additionally, users can compare the current sentiment from previous timeframes. This ranges from 15 minutes to 1 year. In addition to stocks, StockTwits also supports cryptocurrencies and NFTs.

4. InfoTrie – Social Analysis Blended With Financial News  

InfoTrie is a Singapore-based alternative data provider that offers various analytics. In addition to social sentiment analysis, this also includes SEC and regulatory filings and job posting trends. InfoTrie uses natural language processing tools to extract data from leading social media networks. 

It combines the collected data with recent news articles available in the public domain. Some of the key data points include emotions (e.g.bullish), financial language (e.g. dividend forecast), and topics (e.g. mergers). 

All of these data points are packaged together to yield a social sentiment score. InfoTrie covers more than 100,000 companies, alongside indices, ETFs, and commodities. Some of the services that InfoTrie provides include trading strategies, event monitoring, volatility forecasting, and risk management.

5. RavenPack – Advanced Social Sentiment From Unstructured Data Sets 

RavenPack is a social sentiment provider that extracts and analyzes ‘unstructured’ data sets. This means that data is taken directly from the source, without being packaged by third parties. In addition to social media websites, RavenPack also extracts financial news, sell-side analyst ratings, transcripts, regulatory filings, and job postings. 

RavenPack then interprets the data and turns it into actionable insights. We also like that RavenPack provides social sentiment scores on a global basis. This includes everything from the US and Brazil to Egypt, China, and South Korea. RavenPack is also popular for its customizable dashboards. 

This enables investors to view social sentiment data in a user-friendly way. Moreover, users can also track their preferred sentiment tools and receive real-time updates when a metric is triggered. RavenPack does not display pricing on its website. That said, new users can request a trial account to take the dashboard for a test drive.

Conclusion

Social sentiment analysis is increasingly becoming popular with institutional investors and hedge funds.

Retail clients can also gather social insights by using AltIndex. The platform offers valuable data sets on many social metrics, including mentions, follows, likes, and overall sentiment.

AltIndex offers a free plan that tracks thousands of stocks and cryptocurrencies.

References 

https://www.wsj.com/market-data/quotes/AAPL

https://www.cnbc.com/quotes/META

https://www.cnbc.com/2021/04/28/dogecoin-price-surges-after-tweets-from-elon-musk-and-mark-cuban.html

https://altindex.com/ticker/BAC/twitter-mentions

https://www.finra.org/investors/insights/social-sentiment-investing-tools

https://www.bbc.com/news/business-60255088

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