Reddit cryptocurrency predictions
A plunge in the value of Bitcoin this week may have been sparked by crypto-investors selling off their digital currency, experts have said. The price of a single Bitcoin crashed by double-digit percentages between Sunday and Monday, marking the largest two-day dip since March , Bloomberg reported. The value of the decentralised crypto is famously volatile, and can shift wildly in a short space of time. Bitcoin prices surged in recent months , seemingly linked to increased use by institutional investors and financial firms such as PayPal and Square. Regardless, Bitcoin was still up more than percent in the past 12 months. Bitcoin keeps crashing.
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- 3 Predictions for the Crypto Market in 2022
- Reddit's AMC, GameStop surge happened because of anger over Wall Street
- Reddit Co-Founder: By the End of the Year ‘Ethereum Will Be at $15,000’
- NFTs, stablecoins and the value of Bitcoin: Predictions for crypto assets in 2022
- Top Crypto Influencers To Follow In 2021
- Bitcoin/Cryptocurrency price 2022: What experts predict and suggest to keep your money safe
- Voyager CEO Steve Ehrlich's 2021 Crypto Predictions
- 4 Altcoins to Watch Closely in October
3 Predictions for the Crypto Market in 2022
Cryptocurrencies have recently received large media interest. Especially the great fluctuations in price have attracted such attention. Behavioral sciences and related scientific literature provide evidence that there is a close relationship between social media and price fluctuations of cryptocurrencies.
This particularly applies to smaller currencies, which can be substantially influenced by references on Twitter. Here, we show that fluctuations in altcoins can be predicted from social media. In order to do this, we collected a dataset containing prices and the social media activity of altcoins in the form of , tweets over a timeframe of 71 days. The containing public mood was then estimated using sentiment analysis.
To predict altcoin returns, we carried out linear regression analyses based on 45 days of data. We showed that short-term returns can be predicted from activity and sentiments on Twitter. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the paper and its Supporting Information files.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist. Until a few years ago, cryptocurrencies hardly received any public attention.
Only few people had heard about Bitcoin, if at all. It seemed that all of a sudden, Bitcoins were perceived as the currency for illegal purposes. Today, cryptocurrencies increasingly assert a place in the awareness of society and the public. This is accompanied by an increasing research interest. Thus, a rising number of studies have placed their focus on Bitcoins and cryptocurrencies in general.
Two questions that many of these studies address are: How are returns of cryptocurrencies determined and is it possible to predict them? As for traditional commodities, there is reasonable evidence to suggest that cryptocurrency returns are somehow connected to public perception.
Cryptocurrencies tend to be highly volatile which makes them sensitive to external factors. In such a scheme, chosen cryptocurrencies are purchased in small, inconspicuous amounts in a certain time range.
In total, these purchases then add up to a substantial amount. Secondly, these cryptocurrencies are then heavily promoted via social media, which leads to purchases by other parties. The corresponding price increases provides the persons initiating the scheme with very high returns. Altcoins are easier to influence and are thus of special interest in this study.
Another factor that suggests a connection between cryptocurrency returns and social media is based upon theories of behavioral sciences. Social media platforms such as Twitter can be seen as a collective indicator of thoughts and ideas but also of public mood [ 4 ]. Positive mood states lead to more optimism towards investment decisions [ 5 ]. Thus, social media might be a good prediction indicator for investments in cryptocurrencies, of which the extents are reflected in their prices.
While there are all sorts of social media information available, we believe that it is especially the short-term variability of Twitter that makes the platform a very suitable indicator for short-term predictions.
Furthermore, unlike services such as Google Trends, Twitter does not solely provide information about activity but also about the associated mood. Fig 1 illustrates the price and the social media activity which is represented by the number of tweets for the cryptocurrency PinkCoin. At first glance, one would suspect a connection. In the scope of this work, we wanted to pay closer attention to these indications.
Over a time range of 71 days, we collected a dataset covering altcoins. In terms of the scientific literature, this is an unparalleled achievement.
Based upon this data, we ran linear regression analyses in order to create short-term prediction models. The aim of these models was to analyze whether it is possible to predict altcoin returns based upon social media activity. The activity was measured by the number of tweets that referred to a certain altcoin and the sentiment that they contained. We therefore hypothesized that it is possible to predict the return of an altcoin based upon the number of tweets that are referring to it and the sentiment contained in said tweets.
The scientific interest in cryptocurrencies is relatively new. However, there is some related work in existence. Some papers deal with Bitcoin users [ 6 — 8 ], Bitcoin in general [ 2 , 9 — 13 ] or the market dynamics of cryptocurrencies [ 14 — 16 ].
Fewer papers have have analyzed the relationship between cryptocurrency prices or returns and social media activity. While some authors have based their analysis on online forums [ 17 , 18 ], Google Trends and Wikipedia [ 19 ] or social media platforms like Reddit [ 20 ], others have used data provided by Twitter [ 21 ]. Authors such as Garcia and Schweitzer [ 22 ] have even created a framework to bundle several social and economic signals in order to predict the return rates of Bitcoins.
Kristoufek [ 23 ] has investigated the most frequently claimed drivers of the Bitcoin price. Several authors argue that Bitcoins, consequently cryptocurrencies in general, have mainly been addressed in a speculative frame [ 7 , 24 , 25 ]. Therefore, one could say it may be justified or even more appropriate to treat cryptocurrencies much like stocks rather than fiat currency.
Both studies have used tweets including certain expressions of mood. While Bollen et al. While we were assessing the above-mentioned literature, we came across a few things that stood out. No cryptocurrency-related paper, except for one, has considered other cryptocurrencies than Bitcoin in their analyses. This might be due to the superior interest in Bitcoin, or there may even be a more trivial reason: many people may not even know of the existence of other cryptocurrencies.
Secondly, all cryptocurrency-related papers have only focused on daily prices. Cryptocurrencies tend to be extremely volatile. Therefore, considering intraday prices would allow a more granular, detailed picture.
It is also notable that among all papers the sentiment analysis approaches vary. Some authors [ 4 , 21 ] have assigned tweets a class positive, neutral, negative and have used the number of tweets of each for their analysis. Other authors such as Kim et al.
There are many more studies in existence that have attempted to predict stock market prices using different factors. Especially the prediction using public sentiments seems to be of superordinate interest. For example, some authors have also used sentiments on Twitter [ 28 — 33 ] whereas others have used sentiments from stock message boards [ 34 , 35 ]. However, the scientific interest in cryptocurrencies is relatively new and therefore, there are only a small number of studies. This is understandable because cryptocurrencies as we know them today started to exist with the appearance of Bitcoin, which is less than ten years ago [ 36 ].
Based on these grounds, we aimed to expand the field by increasing the quantity of cryptocurrencies included in our analyses. In order to do this, we collected data of the largest altcoins. We also paid attention to the emotional value of tweets pertaining to cryptocurrencies. We showed how Twitter activity and sentiment could be used for some currencies to predict altcoin returns.
This is the first time that small cryptocurrencies have been rigorously investigated for their prediction potential based on Twitter. To further support this growing field, we share the collected dataset with the scientific community in the Supporting Information S1 File.
For this work, we collected altcoin prices and social media activity of altcoins over a period of 71 days in total. Both, prices and social media activities were updated every three hours to also allow for short-term analysis. These datasets are not continuous but split into two time periods. The first period starts on March 21 and ends on May 5, and thus covers 45 days. The data collected in this range represented the training set.
The second period covers 26 days and starts on May 9 and ends on June 4, The data obtained in this range functioned as the test set. This set was used to evaluate the models based on the training set. The ratio of these sets is around 1. In total, our datasets include prices for different altcoins and , tweets referring to them.
All datasets were collected in a legitimate manner, fully complying with the terms of service of the sources in use. The sources of our data will be explained in the next sections. Using this, one can directly crawl Twitter data including usernames, hashtags, tweets, the associated timestamp of tweeting and the number of retweets. In our case, a query referred to a certain altcoin. This was done by using the official currency codes. We collected tweets that were retweeted just as we collected tweets that point to several altcoins.
This was to ensure, that the picture that was presented to the twitter community, gets reflected in our data corpus. Due to restrictions placed by Twitter it was only possible to gather a random sample of up to tweets per query resulting in updated social media activity every three hours for each altcoin. Queries were processed at three-hour intervals and contained up to tweets that had been posted since the last query. For each query, we saved all tweets and the total number of tweets.
In order to extract the sentiment expressed in a tweet, we applied VADER, a valence-based sentiment analysis model that especially addresses the analysis of social media text such as tweets [ 38 ]. Tweets often contain language variation and show the frequent usage of emoticons, abbreviations or slang [ 39 ].
These special characteristics lead to particular requirements when it comes to sentiment analysis in order to avoid information loss. VADER meet these demands by relying on lexicons that contain Western-style emoticons and sentiment-related acronyms [ 38 ]. However, there are several other sentiment analysis approaches in existence that will lead to a similar outcome.
When applying VADER for sentiment analysis, four different scores are computed: positive, neutral, negative and compound.
Reddit's AMC, GameStop surge happened because of anger over Wall Street
The algorithm could help market regulators predict and prevent cryptocurrency schemes that sees traders spend seven million US Dollars per month, only to find the price of their purchased currency falls as the scheme unfolds. Pump-and-dump schemes are used to artificially inflate the price of a cryptocurrency — types of virtual currency - so that scheme organisers can sell the currency at a profit. Long used by traditional financial markets, pump-and-dump schemes are now common in crypto financial markets too. Pump-and-dump scheme organisers often use their knowledge to gain from pump-and-dump events at the sacrifice of fellow pumpers, and the practice costs the cryptocurrency market seven million USD per month. Deceived by the scheme, many investors rush into purchasing certain coins and lose money. Now, for the first time, researchers at Imperial College London have studied pump-and-dump schemes as they happen and developed a machine learning algorithm that could help market regulators predict and prevent this type of market manipulation. An initial draft of the paper is published on arXiv.
Reddit Co-Founder: By the End of the Year ‘Ethereum Will Be at $15,000’
For one, new crypto applications like non-fungible tokens NFTs gained ground, with sales of these digital assets setting new records at major auction houses. Secondly, Bitcoin made strides towards mainstream acceptance, with major websites like Expedia and Microsoft accepting the coin as a means of exchange. Third, in September, El Salvador became the first country in the world to accept bitcoin as legal tender. There are many more examples of how the market for cryptocurrencies has expanded just in the last year. Understanding what motivates individuals to adopt Bitcoin has been a challenge for researchers. Other studies have added more nuances to this argument by considering gender, age, and educational level as equally important factors. The conditions in the crypto space have made it increasingly likely that Bitcoin will become mainstream in the near future. Second, there has been an explosion of new crypto-exchanges — or trading platforms where one can exchange fiat currency for crypto — and major investments into the technological infrastructure of existing exchanges.
NFTs, stablecoins and the value of Bitcoin: Predictions for crypto assets in 2022
Over the past couple of years, cryptocurrencies have gone from being a niche hobby restricted to a few tech-oriented people around the world to a legitimate form of asset class recognised by some of the largest corporations around the world. The prices of cryptocurrencies have blown up over the past few months with many cryptocurrencies reaching record prices in the March-April period of However, more recently, a fairly unknown cryptocurrency called Zoo Token has been trending in the crypto community. Over the past 24 hours, the Zoo Token price has gone up by 32 per cent. Read on to know more about how to buy Zoo Token and Zoo Token price prediction.
Top Crypto Influencers To Follow In 2021
Many companies featured on Money advertise with us. Opinions are our own, but compensation and in-depth research determine where and how companies may appear. Learn more about how we make money. The interest rate on a year fixed-rate mortgage ticked down to 3. That's a modest 0.
Bitcoin/Cryptocurrency price 2022: What experts predict and suggest to keep your money safe
Despite being the difficult year that it was, it resulted in an excellent year for the crypto and blockchain industries. I predict that will be the year of mass adoption of crypto, as the U. Smart contracts will rise with greater utilization, and as the crypto world takes off, retail investors will switch from traditional banks to crypto services. So, here are my top crypto predictions! In we saw the beginning of the mass adoption and widespread financial disruption from the crypto world. Major companies entered the space and have inspired more to do the same.
Voyager CEO Steve Ehrlich's 2021 Crypto Predictions
During the last couple of weeks of January and February, the bitcoins are swinging between k to k. Amp is a top performer this year Nick's Bitcoin prediction is for prices to reach as high as 0, next year, but expects it to reach at least 0, Gold is one of the most well established and mature markets around when it comes to investable assets. A bunch of sources released price predictions for this year, I collected the ones that I was aware of with links.
4 Altcoins to Watch Closely in OctoberRELATED VIDEO: 8 Best Cryptocurrencies to Invest in According to Reddit!
These are the core obsessions that drive our newsroom—defining topics of seismic importance to the global economy. Our emails are made to shine in your inbox, with something fresh every morning, afternoon, and weekend. In , a new cryptocurrency, Dogecoin, was minted as a joke making fun of the speculative frenzy surrounding Bitcoin. Then last August, an anonymous developer created the Shiba Inu coin, the canine mascot for Dogecoin, riffing off the previous prank. Somewhere along the way, the internet gags became very real.
The Blockchains have flooded the finance panorama and the financial ecosystem is replete with segregated individual mini tokens that have made the cryptocurrency ecospace quite fragmented. With a special focus on giving momentum to cryptocurrencies, FTX has emerged as a novel exchange in the cryptocurrency segment. FTX Token offers traders a unique pedestal that inspires their loyalty and offers power-packed features that are unheard of in conventional cryptocurrencies like Bitcoin, Ethereum, Bitcoin Cash, and others.