Social Listening and AI Deep Learning Able To Predict Crypto Volatility
The Race To Control Public Opinion
By Cameron Palmer, 22
CMCI Studio, University of Colorado Boulder
Social media is a gigantic umbrella term that nobody can precisely define. Twitter. Reddit. Facebook. 4Chan. You name it. It doesn’t matter if it’s a worldwide platform or a tiny forum chat; if it spreads messages to different users over the internet, it’s social media.
On sites like Twitter, users are separated into tiers of opinion authority based on followers and likes. Those that achieve the greatest opinion authority are recognized with the coveted blue checkmark. These blue checkmarks are a badge of authority, which causes influencers recognition to continue growing exponentially. This process has made some social media accounts so powerful that they now have the unique ability to influence stock and crypto prices with something as simple as a tweet.
Here are some prominent examples:
Celebrity Tweets That Caused Market Volatility - Timeline
Created by Cameron Palmer, www.beautiful.ai
I aim to understand if social media data analytics, aka “Social Listening,” can be used to intentionally and effectively influence the public sentiment of a targeted coin or stock.
To accomplish this, I will apply insights from personal deep-dive research of “emotional data intelligence” companies like Stockpulse, actionable insight companies like S2 Research, and multiple collegiate studies regarding the relationship between social media influence and market volatility.
Ultimately, this study aims to illustrate a new important framework for thinking of machine learning concepts like “Social Listening” and “emotional data intelligence.”
I will also open a discussion challenging the ethics of new concepts like “emotional data algorithms” and “Digital Language Processing” (also known as “sentiment analysis”) as cited by Stockpulse CEO Dr. Stefan Naan. New technological phenomena have catapulted the study of Social Listening into a truly powerful tool for predicting price volatility and public opinion.
TABLE OF CONTENTS
- What is Social Listening?
- How Does Social Listening Affect Market Prices?
- How Is Social Listening Calculated?
- Why Is Social Listening Important?
- Epidemic-Like Spreading of Social Media Investment Ideas
- The Case of Elon Musk and Dogecoin
- What is Emotional Data Intelligence?
- How Do Emotional Data Intelligence Insights Impact Cryptocurrency Prices?
- Using EDA’s To Track The Epidemic-Like Spread of Investment Ideas
- Challenging Ethics
- Corporate Propaganda or Revolutionary Rhetoric?
- Considering Advancements of Social Media Analytics from the Legacy Perspective
- Defending Emotional Data Algorithms (EDA’s)
- Sources Cited
I will be examining how “Social Listening,” celebrity influence, and the advent of “Emotional Data Algorithms” (EDA’s) can all be used to predict and affect price volatility. Before starting this research, my initial personal dogma leaned on the idea that social media is just unpredictable chaos. I thought, “nobody can keep track of it all.” Like most people, I believed that nobody could control and manipulate social media data.
“Why bother worrying about it?” Right?
The evidence that I found proved otherwise. Rapid developments in machine learning, social media data collection, and predictive algorithms have proven that it is possible to organize social media chaos into actionable market insights.
It’s nothing to hide from; we all trust countless different celebrities, influencers, and public figures implicitly. As technology grows exponentially, many social influencers will inevitably jump onto the bandwagon with outspoken cries of endorsement. Many younger digital natives grew up learning from influencers on sites like YouTube, TikTok, or Vine. We place great trust in many influencers and celebrities, believing their intentions to be honest.
It is common for people to look to popular icons as sources of immense inspiration, treating them as our own personal “digital role models.”
This isn’t necessarily a bad thing. As with most things, it’s complicated. These social media figures guide us in ways that people in our real lives sometimes can’t. It is likely that they primarily give people well-intentioned advice. However, there are also a great many trusted influencers that have sold out their audiences to pump assets and grow their portfolios.
You cannot believe everything you read.
What is Social Listening?
Social listening is defined as “Social media measurement and social media analytics; a way of computing popularity of a brand or company by extracting information from all social media channels, such as blogs, wikis, news sites, micro-blogs such as Twitter, social networking sites, video/photo sharing websites, forums, and message boards.” (Wikipedia)
Take the study of movie fandoms like Star Wars as a good example of powerful social listening. Star Wars has a notoriously passionate legion of fans. You’ve seen them; they are a mighty unit that is occasionally hostile and extremely influential. The opinion of that specific group of viewers is critical to the success of Disney movie producers and the longevity of their careers. The views of these fans can set the groundwork for the film’s long-term legacy. As such, predicting the behavior of fandoms is an increasingly sought-after commodity in the film industry.
Movie fandoms are just one small example of how social listening has become a high-value area of study. As newer, more disruptive technologies become increasingly powerful, those that influence sentiment about them also become increasingly powerful. Convincing large groups of entertained consumers to buy action figures and posters is one thing. Using social influence to guide people towards potentially risky investments is a far more questionable practice.
How Does Social Listening Affect Market Prices?
Social Listening becomes exponentially more profound when you tie in its relationship to the world’s two largest financial revolutions, Blockchain technology and “Reddit-Driven” investing into meme stocks like AMC and Gamestop. According to the Nasdaq, “By monitoring and analyzing data from social media sources — especially concerning communication about stocks — it’s now possible to connect the dots between sentiment and market movements.” (Nasdaq 2020) The largest stock exchange in the world has perked its ears up to the weight that social media has on market prices.
The results suggest that our quantitative understanding of Social Listening insights influencing public perception is more advanced than most people realize. The surface level correlations are quite apparent after compiling examples of celebrity/influencer tweets causing market fluctuations. It’s the hyper-specified data-driven insights and how they are used that are of larger importance.
André Kostolany, a stock market investor who became one of the most successful investors of the 20th century, says that “Facts only account for 10% of the reactions on the stock market; everything else is psychology.” (Nasdaq 2020) Wealthy and influential public figures worldwide are now consciously aware that they have a strong ability to manipulate public sentiment. Many celebrities have learned how to instantly incite revolution or pump their favorite coins and stocks with just 280 characters.
How Is Social Listening Calculated?
Now that you know what social listening is in a general sense, you’re probably wondering how the heck people can make sense of all that data. I found a company that serves as a strong example of social listening in action: Lunar Crush.
Lunar Crush is a social listening and crypto analytics company that allows you to track the social mentions and public perception of specific cryptocurrency tokens in real-time. They create detailed rankings of crypto coins based on overall “Social Dominance” data-driven insights.
Their site explains that “Social Dominance calculates the “share of voice” across all social media data. This is similar to Market Dominance; however, instead of dividing a coin’s market cap by the entire cryptocurrency market, we divide a coin’s social volume by the entire cryptocurrency market’s social volume.” (Lunarcrush 2021)
Bitcoin Social Volume: 1,000,000 mentions
Entire Cryptocurrency Market Social Volume: 10,000,000 mentions
1,000,000/10,000,000 = 10%
Bitcoin Social Dominance in this example would be = 10%” (LunarCrush)
Data insights powered by Social Listening data give investment analysts the ability to make decisions based almost solely on the number of times a specific coin has been mentioned across much of social media. LunarCrush is essentially monetizing its ability to calculate and present Social Dominance scores. For the record, I am currently testing LunarCrush’s system to see how it works for my investments. None of this is financial advice.
Why Is Social Listening Important?
It is certainly acceptable to seek occasional guidance from digital role models.
Still, we must indeed hold them accountable for their influence as well. Our attention is a commodity, and we must be picky with whom we choose to reward it.
I reached out to the SEO of S2 Research, Matt Seltzer, a Marketing Research & Strategy Consultant, to ask him about the existing relationship between Social Listening and Actionable Insight Marketing. My research goal was to determine how specific the insights from social listening are in a real-world application. Matt told me, quote, “The whole concept you’re talking about is looking for trends that you can capitalize on for your marketing.”
He also shared a great real-world example of hyper-targeted data insights. Matt said, “Arby’s does a great job with this. They tap into super-niche audiences they find through data, create specified content for them, and hyper-target it on social media. They make videos of Arby’s Sauce packets doing marching band every year during the marching band finals in Indianapolis, for instance.” (Seltzer 2021). Ultimately, it’s very clear that social listening can be used to create “hyper-targeted” advertisements directed at increasingly specific demographics.
If you want to learn more about actionable insight marketing, check out S2 Research
A New Gold Rush For Data Analytics
In this digital age, public sentiment is everything. With it, nothing can fail; against it, nothing can succeed. Whoever molds public sentiment goes deeper than he who enacts statutes or pronounces judicial decisions. Social media influencers, celebrities, and public figures are the weavers of our shared narrative. Thus it is imperative to understand the magnitude of their influence.
These claims of Social Listening’s newfound importance are backed up when German “emotional data intelligence” company Stockpulse says, “While the technologies themselves may not be new, the interest from exchanges and banks is. To date, the tech companies leading the software development have largely served hedge funds, seeking a competitive market edge. Major exchanges have now jumped on board.” (Stockpulse 2021).
The technology to predict and plan for shifts in public sentiment already exists, made readily available using predictive algorithms and data collection. Major institutions and titans of industry are already instituting these quantitative analysis protocols. That being said, most people are still largely unaware that these technologies even exist.
Epidemic-Like Spreading of Social Media Investment Ideas
Universities worldwide have conducted several highly relevant studies to gauge whether celebrity influence over the stock and crypto markets can be tracked and predicted. The two key points of research methodology used include comparing social media user data to stock market fluctuations.
In simple terms, if someone posts on social media, in particular Twitter and Reddit, algorithms can track if that post has in any way caused a stock graph to trend upwards. People who are good with numbers can follow this and make financial investment decisions based on those results.
Academics at Computer Science University College London wrote in their paper “Mutual Excitation Causing Market Volatility” that, “Data favors a more epidemic-like definition, describing a price fluctuation as occurring by psychological contagion, where the news of price increases spurs investors’ enthusiasm which spreads contagiously and brings in a larger group of investors, drawn in by envy and excitement about the previous price rises .” (Phillips and Gorse 2019). Another framework for understanding this is; As celebrities entertain us and make us feel excited, our brains release pleasure chemicals that make us more likely to purchase things and take financial risks.
Popular influencers have realized that their social media accounts are an increasingly powerful financial tool. When celebrities post about exciting “investment opportunities” people begin to flock to the asset because they already hold strong pre-existing positive associations with that celebrity. Furthermore, the online fandoms of that same celebrity start to share and amplify the investment idea until an epidemic-like spread is created. This is why new phenomena like AMC, Dogecoin, and Gamestop are so resilient.
The Case of Elon Musk and Dogecoin
Remember this? https://www.beautiful.ai/-Mdj-qhIFCzdMGqy2j_C/4
An example of this in the crypto arena would be Elon Musk boasting about his love of Dogecoin. Long-term holders of Dogecoin profit greatly off of Elon Musk hype due to the influx of new buyers it generates. Afterward, those same Dogecoin “hodlers” start to engage in an “epidemic-like spread” of posts bragging about their gains and spreading memes. This contagion-style hype spread inevitably causes less experienced investors to buy during bad price points due to FOMO (Fear Of Missing Out).
Dogecoin uses the epidemic-like spread of memes, hype, and influencer backing to create what has miraculously been (so far) a relatively sustainable public asset. The self-proclaimed “meme asset” is a massive disruption to traditional financial systems that is still critically unexplored. It sounds silly, but as of this paper publishing, Dogecoin is worth roughly 58 billion dollars.
Billion. With a “b.”
Important Reminder: These “meme coins,” like Dogecoin, do not have tangible uses or functions. Invest at your own risk.
“Emotional Data Intelligence” Used to Develop “Sentiment Analysis”
Another example of social media influencer posts and public financial sentiment being tracked through machine learning comes from Stockpulse.
Stockpulse is a Machine Learning/AI tech company that has developed data analytics software and algorithms to quantitate social media data into actionable investment insights. They work primarily with what they describe as “Digital Language Processing (DLP), also referred to as “sentiment analysis.”
They describe the self-proclaimed “Emotional Data Intelligence” as “referring to the collection of large amounts of data called data mining. Both parts of Social Media analysis are unstructured and must be processed to create value for financial investors. Stockpulse’s artificial intelligence filters this bulk of information, selects, structures, and converts it into intelligible data for the financial industry. The outcome is Emotional Data Intelligence!” (Stockpulse 2021)
Stockpulse explains that “ Being pioneers and trailblazers at one stage, Stockpulse has become an essential player for the financial industry. Whether it’s some banks or hedge funds, Private Equity, Venture Capital or Family Office, Portfolio Managers or Insurance Companies, Publishing Houses or Stock Exchanges, and Institutional Supervising Agencies. All rely upon Emotional Data Intelligence today.” (Stockpulse 2021)
Dr. Stefan Naan, the CEO of Stockpulse, wrote that “Stockpulse collects and analyzes data from social media sources around the clock in German, English, and Chinese.” He says, “We have historical data from alternative sources that date back to 2011. Our web crawlers are continuously scanning thousands of different Internet sources for relevant financial topics and communication, collecting several million tweets, chat messages, message board posts, news articles, and comments to news articles each day.” (Stockpulse 2021).
This claim is backed up by London academics Phillips and Gorse when they said “web crawlers scan “thousands of different internet sources for relevant financial topics and communication, collecting millions of tweets, chat messages, message board posts, news articles, and comments to news articles each day.” (Phillips and Gorse 2019) The claims about web crawlers collecting massive stores of all social media interactions are purely factual. Many reputable sources echo these claims.
“Emotional Data Intelligence” can be used to create quantifiable rankings of public figures based on the potential to influence markets. Amongst countless other potential applications.
According to the CEO of Stockpulse, in an article written for the Nasdaq, “Some market participants potentially have a higher impact on the movement of stock prices than others.” (Nasdaq 2019) Stockpulse has developed a curated list of verified social media users (including Twitter accounts of CEOs of listed companies, influential politicians, journalists, analysts, and news agencies) and ranked their ability to influence markets using predictive algorithms, data collection, and machine learning.
The applications of such technology go far beyond curated lists. The Nasdaq has ambitions to create easy-to-monitor alert systems based on these results. They said, “In addition to detecting the expert network of social media users for a single stock or industry, an alert system for specific Twitter accounts could be highly relevant. As soon as a Twitter user identified as a relevant and credible source for a stock posts anything about that company, trading surveillance wants to know about it. Having this information as quickly as possible is key.” (Nasdaq 2020). In summary, most legacy financial institutions are already figuring out how to use these emotional data algorithms to their advantage. They are well aware of these “sentiment analysis” or “emotional data intelligence” algorithms (EDA’s).
How Does Emotional Data Intelligence Impact Cryptocurrency Price?
To answer this question fairly, we have to take steps back and look at how the crypto markets interact with social media differently than traditional stocks.
According to Korean scientists Sejung Park and Han Woo Park, in their academic study called “Relations between Reputation and Social Media Marketing Communication in Cryptocurrency Markets,” “Cryptocurrency firms were more actively producing information when there was increased public demand and increased transactions. Posts were more frequent when the coins’ prices were high and less frequent when the prices were low.” (Park and Park 2021) In other words, crypto firms attempt to time their marketing messages to the highs and lows of the market. Allowing public figures to maximize their potential influence over market buys.
This is not a shocking new phenomenon by itself, but now EDA’s give marketers the ability to use this same strategy using Social Dominance metrics instead of loosely timing price volatility. Influencers and brands have become attached to this new, more powerful form of marketing which entices new investors using excitement, hype, and memes. As long as they remember to say, “This is not financial advice,” there’s not any liability.
This is not financial advice. See :)
Gourang Aggarwal, a researcher for NIIT University in India, calculated tangible results for this concept in his paper “Understanding Social Factors Affecting The Cryptocurrency Market.” Aggarwal says, “Opinions of social media influencers having a relationship with crypto-industry (negative) has a correlation value -0.0631 which shows that a negative news story from a big personality or celebrity might drop the cryptocurrency price.” (Aggarwal 2019)
He continues, “media messages that relate to the keywords “cryptocurrency bans” (negative) (the 6th attribute) correlates with a value of -0.1329 and can also lead towards a drop in the price of cryptocurrency” (Aggarwal 2019).
In layman’s terms, it is statistically true that any news about negative buzzwords (aka FUD) like “cryptocurrency bans,” “ChinaBan,” or any other negative sentiment from celebrities generally results in a price drop. Duh.
It gets more insightful when you realize that spreading these messages is a deliberate attempt to use Emotional Data Algorithms to sway public opinion of new emerging technologies and concepts like Blockchain or Decentralized Applications (aka Dapps).
Opponents of cryptocurrencies and the blockchain technology revolution attempt to drain cryptocurrency prices by spreading negative sentiments about the technology, frequently using FUD (fear-based buzzwords) to scare away potential defectors of the legacy system.
Looking at you, governments, central banks, and hedge funds ;)
Using EDA’s To Track The Epidemic-Like Spread of Investment Ideas
The extent to which our personal data is used and commoditized is still a mystery to most people. According to Nasdaq, “People interacting on social media generate emotional data by expressing their emotions and opinions via tweets, forum posts, and blogs. They also consume it, and in the process are influenced by the sentiments, feelings, and opinions expressed by others.” (Nasdaq 2020) Social media data has moved far beyond location tracking and TikTok recommendations. Our applications now can track our emotional habits and influence our opinions with “hyper-targeted” data-driven insights.
For more about the dangers of this concept, check out the Netflix documentary The Social Dilemma.
Concerning cryptocurrency markets, Phillips and Gorse of University College London said that “This work demonstrates how epidemic detection techniques can be applied to social media data to predict cryptocurrency prices and provides some empirical evidence that “bubbles” mirror the social epidemic-like spread of an investment idea.”. (Phillips and Gorse 2019) The concept of “epidemic-like” spread of investment narratives creates the potential intersection between EDA’s and cryptocurrency volatility prediction.
Similarly, Mehrnoosh Mirtaheri, USC Information Sciences Institute, writes about tracking individual coin “pump and dump schemes” in his paper “Identifying and Analyzing Cryptocurrency Manipulations in Social Media.” He says, “Specifically, given financial and Twitter data pertaining to a particular coin, our method can detect, with reasonable accuracy, whether there is an unfolding pump and dump scheme, and whether the resulting pump operation will succeed in terms of meeting the anticipated price targets.” (Mirtaheri 2019). Algorithms and machine learning have developed a method capable of predicting the occurrence of “pump and dump schemes” for specific coins. It can also reasonably predict their chances of success.
Phillips echoes this confident analysis saying that “The authors found the relationship between price and Twitter submissions acts as an amplification mechanism; such amplification mechanisms are a commonly identified component of the propagation of speculative bubbles.” (Phillips 2019).
He explains further that “a positive feedback loop is identified whereby firstly price increases cause search volume to increase, which in turn causes mentions on Twitter submissions to increase, with this, in turn, causing a further price increase.” (Phillips 2019)
These studies cement that social media investment ideas, memes, and fandom hype are quantifiable, predictable, and potentially manipulatable. The technology already exists, and it’s already being used behind the scenes.
Wanna hear another just for fun? John Bollen, a business professor at Ishe Isa University, claimed in 2010 that “Twitter data could predict the Dow Jones Industrial Average with 87.6% accuracy.” (Ogilvy 2021). You can’t make this stuff up. It’s trackable, institutionalized, and capable of being manipulated with relatively frequent success.
Many readers may not appreciate sharing “opinions” on the morality of technological advancements, but I don’t care. As I am constantly deep-diving into the study of philosophy, I find it necessary to challenge the ethics of Social Listening Analytics and Emotional Data Algorithms (EDA’s).
Marcus Aurelius once said, “The more we value things outside our control, the less control we have.”
By trying to control something that isn’t meant to be controlled by man (widespread public opinion), you risk giving that power to an artificial entity much more powerful than any singular man or woman. Should we really give AI access to our “emotional data”?
Friedrich Nietzsche once said, “The surest way to corrupt a youth is to instruct him to hold in higher esteem those who think alike than those who think differently.”
What if these wealthy institutions use these algorithms to create targeted propaganda for children. Sure, the law says you can’t do that. Ask yourself though. Do we have any system of checks and balances capable of stopping these powerful AI’s combined with the influence of legacy institutions? I doubt it.
These are extremely dangerous algorithms that need to be thoroughly examined from a human rights perspective before we allow major institutions to use them.
Corporate Propaganda or Revolutionary Rhetoric?
Revolutionary rhetoric and propaganda are closely related but also fundamentally different.
Both are linked to the epidemic-like spread of messages, as cited earlier. However, the ideas and intentions behind them couldn’t be farther apart.
Revolution, in its purest intended definition, stems from the concept of defending basic human rights. It is the idea that if governments don’t treat their citizens fairly then, they will, and should, band together to demand a system change. This unity is exclusively achieved through the epidemic spread of revolutionary rhetoric.
It’s a fundamental function of the “American dream.” Generally speaking, revolution stems from good intentions. It’s about freedom and equality above all else. Sometimes people go off the rails and break things, set fires, all that crap. That garbage is unfortunate, but it is also an inevitability of human behavior (particularly anger and frustration).
Regardless, revolutions almost always stem from classic American ideals of freedom and fair competition.
In contrast, propaganda stems from ambitions of societal control. Those in power use propaganda to get people to agree with certain philosophies and ideas without ever actually explaining the fundamental concepts. In other words, they expect you to “take their word for it.” Widespread messages of these magnitudes, if followed blindly, if left unquestioned and unsourced, are much more akin to propaganda.
Do not believe everything you read! We must stop expecting to be handed all the answers without having to lift a finger.
Ask yourself about the long-term implications of this relationship between EDA’s and market prices. What happens when someone controls the messages and, simultaneously, the messages control the money?
Suddenly, the system breaks. The world is overrun with mini dictators that tell us all how to believe and how to spend. I will be outlining that the power of social media influencers, if ignored and unquestioned, is potentially a massive hindrance to the concept of “fair competition.”
There are good arguments for seeing this technology as bad for society rather than good. Naan says, “We don’t know anything about the person, but there are metrics with probability scores where you can identify if a person is more important than another person” (Stockpulse 2021). It seems that algorithms determining “human importance” raise potential ethical concerns.
Another potentially harmful development comes from the Nasdaq. They said, “Trading surveillance teams can monitor any rumors or posts about relevant events in real-time in social media and get instant notifications if certain companies or events suddenly move into focus.” (Nasdaq 2020). These power players get real-time access to all the premium data-driven insights. The competition gap between “average joe” investors and wealthy/institutional investors has increased exponentially with the implementation of EDA’s.
On the one hand, politicians, central, hedge funds, and the media use their wealth, power, and influence to make themselves richer and consumers poorer. They often leave investors behind in a vicious cycle of giving one and taking two.
On the other hand, crypto influencers (the reputable ones) use their wealth, power, and influence to promote a new technology with a strong potential to increase financial inclusivity worldwide. The use cases for blockchain technology are next to limitless, potentially fixing countless systemic problems constantly present throughout our lives.
Surely this serves to justify a blockchain system that rewards early adopters and punishes long-term hold-outs.
Considering Advancements of Social Media Analytics from the Legacy Perspective
New technologies and concepts like Social Listening, EDA’s, Blockchain Technology, Data Collection, and CBDC’s (Central Bank Digital Currencies) are all very tricky topics when analyzing from a human rights perspective. I lean towards an Edward Snowden style perspective on surveillance technologies and centralization.
As supplied by countless blockchain innovators, the counter-proposal to a “centralized” governance system is to “decentralize” the entire system by spreading governance power amongst the masses instead of consolidating it to a small group of hyper-powerful men.
The Wall Street Journal challenges the idea of community-driven investing and governance, attempting to dismantle the morality of “Reddit-Driven” meme stocks like AMC and Gamestop.
A panel of their writers said, referring to the Reddit/AMC public spectacle, that “Mass coordination on social media represents a tremendous threat. What occurred over the past few weeks when markets were dislocated and retail investors who “held the line” ended up holding the bag, is merely another example of the madness of crowds.” (WSJ 2021). In summary, an argument is made which claims that public unity through shared message spreading is just another way of saying, “Tremendously threatening mass coordination and a symptom of the madness of crowds.”
Not my cup of tea, but let’s give it a chance. WSJ’s first claim is that Reddit frenzies mess with an already unstable market in ways new for traditionalist investors and, therefore, it’s “not controllable.” They say, “Unlike in value investing, the winners of Reddit-led investing are determined by who gets out at peak speculative mania, a game of financial chicken that less sophisticated investors are sure to lose. Reddit users have employed an aggressive and manipulative investment strategy they might otherwise critique if employed by a hedge fund.” (WSJ 2021). Fair enough. This idea is compelling counter-evidence.
The argument here seems to be that older investors don’t understand the ins and outs of the many deeply linked social media communities in the same ways that the younger generation does. Therefore, they will continue to be on the losing end of the new trading system (trading based on public sentiment and hype).
In simplest terms, old school investors lose out to the digital native generation because they do not understand the memes and don’t know how to ride the market trends properly with the rise of social media. Social media influencers and memes are starting to control the money, and those who don’t partake, lose.
I will counter that while this narrative is compelling when thinking of older investors struggling to keep up with social media trends, The people actually getting hurt by Redditors are not “old school retail investors”. They are institutional powers, wealthy political incumbents, and many other people at the top of the food chain.
If these traditionally oppressive powers come to possess EDA’s, they will have the ability to control public sentiment with extreme precision.
It wasn’t easy to find a solution for the dilemma of fair competition between traditional retail investors and the new influx of digital native investors. The proposed solution I arrived at was to prioritize educating older investors about social media, blockchain, and other aspects of popular media and how it influences investors. You have to play the game to stay in the game if you ask me. Take from that what you must.
One of the WSJ authors, Dan Kim, Georgetown University, accounting and computer science, says that “Mass coordination on social media, or anywhere, is a curse, as it seems to compel people to participate in the madness. The antidote, however, is the educated individual, not the (hammer) of the state.” (WSJ 2021). The sensationalist words used in this quote distract from a potentially shared perspective between both sides. This is also a good example of the consequences of spreading FUD that we see with growing frequency.
Education is key. By educating everyone about these new phenomena, technologies, and disruptive innovations, both young and old, then everyone can have the chance to compete in the new system fairly.
The new proposed decentralized finance and governance system is not exclusive to the hyper-intelligent or the wealthy elite. It is certainly not exclusive to media outlets and meme lords. Old-school investors can absolutely figure out these new concepts and apply them successfully. In return, they wouldn’t have to continue lazily championing traditionally oppressive legacy systems for fear of having to do some homework.
Defending Emotional Data Algorithms (EDA’s)
In defense of the innovators at Stockpulse, their algorithm (EDA’s) claims not to take any personal information into account when determining the “importance “of a social media user. The CEO Naan said, “We don’t know anything about the person, but there are metrics with probability scores where you can identify if a person is more important than another person.” (Stockpulse 2021). Despite this, it’s important to note that the root of ethical issues is not about technology; it’s about the people who control it and use it to manipulate markets. It’s those with ulterior motives that control the technology which needs to be further examined.
Stockpulse explained that “With the growth of social media’s presence in financial markets, it is perhaps only a matter of time before regulators themselves employ NLP and other tools in their market surveillance. Some legal experts said they wouldn’t be surprised if they already have.” (Stockpulse 2021). There are still many essential questions left unexplored even after all the initial technical data research. Is it ethical to track and measure such things as users’ social media sentiment? Is public opinion supposed to be controlled? What are the long-term consequences of leaving these complex algorithms exclusive to big corporations, governments, and hedge funds? If the government uses it, why not private institutions too?
This new framework for understanding Social Listening, EDA’s, and AI Deep Learning might sound alarmist upon initial reading. The point is not to assume that AI, EDA’s, or Social Listening analytics must be manipulated or oppressive. Technology doesn’t automatically function in the interest of malice, as movies like Terminator or War Games classically illustrate.
P.S. Like the idea of NFT Virtual Worlds? Check out a movie called Ready Player One
What if all of these new powerful technologies and algorithms could be used by rehab facilities to help people with addiction? What if scientists used them to develop mental health research in congruence with social media usage data? What if they could reduce the negative psychological impacts of frequent social media addiction in young people?
There seem to be so many more unquestionably ethical applications for this technology that doesn’t just entail making rich investors richer.
Decide for yourself how all of these new narratives and fintech developments fit into your worldview. These are my opinions based on a mountain of reading and academic research.
There are strong reasons to believe that controlled social influence can be harmful and manipulative. There is also strong evidence of strategic social influencing fostering a better widespread understanding of disruptive technologies; promoting a humanitarian alternative to a system with a legacy of oppression.
Further implementation of Social Listening data analytics insights could lead to a deep centralized control of public opinion and social media sentiment. It could also lead to the largest techno-sociological revolution in human history.
It all depends on who’s using it and which side controls more of it. Unsurprisingly, the fate of free will seems to remain in the hands of wealthy influencers and predictive algorithms. The race for control over public opinion is long underway.
1: “How Does Social Media Influence Financial Markets?”
Comment: A kind of warmup article to the idea that we can measure social media’s influence on public spending.
2: “11 Tweets That Turned the Stock Market Upside Down.”
Author: Adam Kornblum — Head of Global Digital Marketing & Vice President for CeraVe at L’Oréal — Linkedin, 2018
Comment: “In this age, in this country, public sentiment is everything. With it, nothing can fail; against it, nothing can succeed. Whoever molds public sentiment goes deeper than he who enacts statutes, or pronounces judicial decisions.” This is a technical analysis of measuring the influence of social media figures or as I prefer to call them “Digital Role Models”.
5: “Opinion | Social Media Enters The Stock Market”
Reuters. The Wall Street Journal, Dow Jones & Company, 9 Feb. 2021, www.wsj.com/articles/when-social-media-enters-the-stock-market-11612914443.
Comment: A highly negative piece surrounding the Reddit stock market influence. Written by the Wall Street Journal, this article attempts to call to attention the worst practices and behaviors of Reddit Influencers.
6. Stockpulse “Emotional Data Intelligence” AI Company
7. S2 Research “Actionable Insights”
Author: Matt Seltzer — Market Research & Strategy Consultant
8. Lunarcrush “Social Listening Crypto Analytics Company”
9. “GameStop: WallStreetBets trader army is back for a second share rally — here’s how to make sense of it”
Author: Larisa Yarovaya
10. Bitcoin Magazine — “GOVERNMENT CENTRALIZATION VS. BITCOIN DECENTRALIZATION”
Author: Ansel Lindneraug
1: “Understanding the Social Factors Affecting the Cryptocurrency Market”
Author: Gourang Aggarwal. “Understanding Social Factors Affecting The Cryptocurrency Market.” NIIT University, 2019.
Comment: This scholarly paper focuses on the importance of differentiating the approach towards social media influence on volatility for the stock and crypto markets. Basically, we can’t analyze social media influence on volatility the same for crypto as we do for the stock market. It just doesn’t work the same way.
2. “Relations between Reputation and Social Media Marketing Communication in Cryptocurrency Markets”
Authors: Sejung Park and Han Woo Park. Korean Scientists — The Korea Content Associations, 2020.
Comment: “This study demonstrates useful visual analytics with Tableau in conjunction with semantic network analysis using examples of sentiment flow and strategic communication strategies via Twitter in a blockchain domain.” (Abstract) This paper is fundamental to support paper. These scientists figured out how to measure the relationship between information production and can successfully measure social media public sentiment.
3: “Identifying and Analyzing Cryptocurrency Manipulations in Social Media”
Author: Mehrnoosh Mirtaheri. USC Information Sciences Institute, 2019.
Comment: “In this work we propose and evaluate a computational approach that can automatically identify pump and dump scams as they unfold by combining information across social media platforms. We also develop a multi-modal approach for predicting whether a particular pump attempt will succeed or not. Finally, we analyze the prevalence of bots in cryptocurrency-related tweets, and observe a significant presence of bots during the pump attempts.” This quote summarizes this paper perfectly. Very important to my research.
4: “Cryptocurrency Price Prediction Using News and Social Media Sentiment”
Author: Connor Lamon — Stanford, 2020.
Comment: “This project analyzes the ability of news and social media data to predict price fluctuations for three cryptocurrencies: bitcoin, litecoin and ethereum”. By the end of this scholarly paper from Stanford, these researchers claim that their predictive algorithm can predict (with 86% accuracy) Bitcoin, Ethereum, and Litecoin price volatility using data from social media.
5: “The Predictive Power of Social Media within Cryptocurrency Markets”
Author: Phillips, Ross Christopher — University College London, 2019.
Comment: This is a doctorate thesis that dives super deep into data-driven analytics of social media influencing short, medium, and long-term volatility. Really insightful and super long. Most of it is technical, but the author raises lots of enthralling discussion points. Especially interested in his overall takeaway that social media has a much higher correlation with long-term crypto prices rather than a short or medium term.