Jack  C

Jack C

1648089867

Cryptocurrency Fan Tokens

In this post, you'll learn What Is a Cryptocurrency Fan Tokens & How Do They Work?

As the world continues to digitize, and different sectors and industries become more reliant on technology, they begin to look at the next generation of digital technology. Within the sporting realm, digitalization has been directly felt with the emergence and rapid growth of e-Sports, but even traditional sports are getting online more.

The ability to leverage digital and new technologies is allowing sports teams, and the accompanying businesses, to engage and monetize their fan base further. Sports teams are also realizing that the need for secondary revenue streams has never been more important. It is through the digitalisation of fan experience and engagement that this can be met. As the world becomes more digitized, so the consumers also look for more digital solutions — and sports fans are no different.

Blockchain Fan Tokens are one such wave sweeping the sports world. They have already started gaining traction at some of the world’s biggest sports teams; UFC, FC Barcelona, Juventus and PSG are just a few examples of major teams and organisations already reaping the benefits of blockchain fan tokens.

Fan tokens are cryptocurrencies that permit their holders to access a variety of fan-related membership perks like voting on club decisions, rewards, merchandise designs and unique experiences. They can be used by sports clubs, music fan clubs and other organizations to democratize and organize experiences, establish club leadership and more. 

Unlike NFTs, fan tokens are completely “fungible” or interchangeable. This means that, just like fiat or cash, the tokens can be exchanged for sports club merchandise, VIP experiences and more. Additionally, they play an important role in tightening the club community with another team-branded piece of fandom.

Fan tokens are cryptocurrencies that aren’t necessarily backed by underlying value principles of Bitcoin or Ethereum. They receive their worth from how much fans value being able to participate in the club and earn unique benefits.

What are Fan Tokens?

So, what is a fan token? The term ‘fan token’ is quite explanatory as it refers to a token, which can represent value and ownership, that a fan of a specific sports team, owns and gains value from. From this simple explanation, there is a broad spectrum of uses and benefits.

These tokens are finite digital assets that can be bought, sold or exchanged by fans to create a team-based economy. They can also then work as a currency and be interchangeable for merchandise, collectables or exclusive interactions.

For the user of these fan tokens, there is no confusing blockchain or cryptocurrency interface to worry about as they are as basic as points on a mobile app that can be topped up or awarded. It is the back end that holds the powerful technology that never needs to interact with the fans.

In a blockchain sense, there are utility tokens, and there are security tokens. The Fan Token is usually a utility token and this again gives a hint at what these tokens can offer — utility. Tokens created on a blockchain can be programmed to have many different uses for the fans and can offer exciting benefits and bonuses not possible elsewhere.

Other than just the monetization of these tokens for use in a fan token economy, the blockchain aspect of these tokens means they can be used for non-critical voting and other levels of engagement.

But there are benefits and utilities too that are currently unmatched without blockchain technology in sports. Most importantly, this new team-based economic ecosystem can turn into a new revenue stream for teams. The creation of these tokens, for instance, can provide a massive capital boost when they are first sold. For example, Barcelona’s fan token sold out, and earned them $1.3 million, in less than two hours.

By offering new forms of engagement with fans, fan tokens are incentivized to be used for buying merchandise, entering competitions, and even voting in polls and other non-critical or collaborative decisions — such as which song is played when a goal is scored.

Why use blockchain?

Tokens are nothing new, and using a traditional token in a sports team setting is quite possible, but the recent boom in these tokens has come off the back of blockchain technology for a very good reason. Blockchain use cases in sports offers an already-made, and programmable, economy through the distributed ledger. Furthermore, the tokens have a vast utility that can be enacted without the need for intermediaries or additional cost and effort.

The token economy and distributed ledger enables the fan tokens to be monetized similarly to Bitcoin, but the utility of the token also means that they can be used for voting rights, fan, sponsorship and ownership engagement as well.

Blockchain is also well regarded for its community and democracy and for this reason, blockchain in the sports industry makes sense. For a sports team and a fan base, this is well suited. Putting forward a fan token for a team emboldens the community spirit and creates a stronger sense of belonging through added engagement.

This visible community spirit and a higher level of engagement can also act as a lightning rod to new fans, and fans from across the globe. It is a new method of engagement for fans that have not got the opportunity or access to be a part of the team, other than through digital engagement. It suddenly becomes a lot more than just attending matches in the given city.

How Do Crypto Fan Tokens Work?

Crypto fan tokens work fairly similarly to a regular cryptocurrency. First, you research the fan token you want to buy, head to a cryptocurrency exchange that lists the token, and make your purchase.

And, like other cryptocurrencies, crypto fan tokens are subject to the whims of the crypto markets. That is, they're volatile and are just as likely to rise as to fall, and there is absolutely no guarantee that you'll end up with any money at all.

Crypto fan tokens mean different things, depending on the project.

The world's largest cryptocurrency fan token site is currently Socios, which enables sports clubs to create cryptocurrencies for their supporters. For example, on Socios, you'll find crypto fan tokens for soccer clubs like Manchester City, Paris St. Germain (PSG), and Juventus, Formula One teams Aston Martin and Alfa Romeo, eSports teams like Heretics and OG, cricket clubs from the Indian Premier League, the New England Patriots, and more.

Indeed, Lionel Messi's PSG signing fee included some of the club's cryptocurrency fan tokens!

Once a user buys crypto fan tokens for their favorite team (or even just as an investment), they gain the chance to vote on various matters at their club. There is no set list of matters applicable to each and every club issuing crypto fan tokens, but some of the options include:

  • Club bus designs
  • Dressing room designs
  • Music played after scoring a goal/points
  • Playing a message in the dressing room before the game
  • Ticket raffles/rare merchandise drops
  • Exclusive fan token content

But Socios isn't the only site offering crypto fan tokens for sports clubs. You'll also find crypto fan tokens on Binance, where you can buy crypto fan tokens for three soccer teams at the time of writing.

How to Identify a Fan Token

Fan tokens generally are used as a part of fan clubs and sports clubs. They differ from other cryptos like Ethereum or Chainlink because they don’t solve the same financial or technical problems. In other words, they are more of a fun, rewards-based token.

Should You Buy Crypto Fan Tokens?

As with any cryptocurrency investment, cryptocurrency fan tokens are a risk. A 2021 BBC report found that soccer fans had pumped $300 million into cryptocurrency fan tokens, though some tokens have decreased massively in price since their launch.

Crypto fan tokens for Manchester City (UK) and Lazio (Italy) dropped by 50% and 70%, respectively, though both from relatively high launch prices.

That said, some of the fan tokens have delivered better returns than Bitcoin, with tokens from Inter Milan (Italy) and Trabzonspor (Turkey) offering better gains than Bitcoin throughout 2021.

Furthermore, in many cases, the issuing sports club or team holds onto a large percentage of their tokens, distorting the market. The BBC report found that the top 13 clubs on the Socios platform hold a total of $1.9 billion worth of tokens, yet fans only own $367 million. The clubs issuing the tokens hold massive power over any potential investors, which is something any potential crypto fan owner should consider.

Finally, the rewards for crypto fan tokens linked to sports are limited in their scope. Experts believe that the balance of risk to rewards (i.e., how much you must invest to get a say in the running of the club) is also severely slanted towards the clubs, which effectively incur zero risk.

How to Buy Fan Tokens

Fans must purchase CHZ via a crypto exchange in order to acquire fan tokens that exist on the Chiliz network. However, there are fan tokens that exist outside of Chiliz and their Socios.com website.

These tokens  are specific to a team or club and  are rare digital assets that provide access to an encrypted ledger of voting and membership rights ownership. CHZ tokens can also be used to purchase and trade different fan tokens on Socios.com. Fan tokens can be traded on Chiliz.net – their in-house exchange and trading platform against CHZ.

Some fan tokens are available on popular centralized exchanges, but some may not be certified or large enough to be listed yet. In this case, fan tokens could only be available for trading or swapping on decentralized exchanges (DEX) like PancakeSwap. You will need to have a cryptocurrency to trade for fan tokens on DEXs. 

You can currently buy the largest fan token, Chiliz on platforms like: Binance.com, Huobi Global, Coinbase Pro, Bithumb, KuCoin, Chiliz

Read more: What is a Crypto Airdrop | How to Find Them

🔺DISCLAIMER: The Information in the post isn’t financial advice, is intended FOR GENERAL INFORMATION PURPOSES ONLY. Trading Cryptocurrency is VERY risky. Make sure you understand these risks and that you are responsible for what you do with your money.

I hope this post will help you. Don't forget to leave a like, comment and sharing it with others. Thank you!

#bitcoin #tokens #cryptocurrency #blockchain 

What is GEEK

Buddha Community

Cryptocurrency Fan Tokens
Amara Sophi

Amara Sophi

1593680226

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Words Counted: A Ruby Natural Language Processor.

WordsCounted

We are all in the gutter, but some of us are looking at the stars.

-- Oscar Wilde

WordsCounted is a Ruby NLP (natural language processor). WordsCounted lets you implement powerful tokensation strategies with a very flexible tokeniser class.

Are you using WordsCounted to do something interesting? Please tell me about it.

 

Demo

Visit this website for one example of what you can do with WordsCounted.

Features

  • Out of the box, get the following data from any string or readable file, or URL:
    • Token count and unique token count
    • Token densities, frequencies, and lengths
    • Char count and average chars per token
    • The longest tokens and their lengths
    • The most frequent tokens and their frequencies.
  • A flexible way to exclude tokens from the tokeniser. You can pass a string, regexp, symbol, lambda, or an array of any combination of those types for powerful tokenisation strategies.
  • Pass your own regexp rules to the tokeniser if you prefer. The default regexp filters special characters but keeps hyphens and apostrophes. It also plays nicely with diacritics (UTF and unicode characters): Bayrūt is treated as ["Bayrūt"] and not ["Bayr", "ū", "t"], for example.
  • Opens and reads files. Pass in a file path or a url instead of a string.

Installation

Add this line to your application's Gemfile:

gem 'words_counted'

And then execute:

$ bundle

Or install it yourself as:

$ gem install words_counted

Usage

Pass in a string or a file path, and an optional filter and/or regexp.

counter = WordsCounted.count(
  "We are all in the gutter, but some of us are looking at the stars."
)

# Using a file
counter = WordsCounted.from_file("path/or/url/to/my/file.txt")

.count and .from_file are convenience methods that take an input, tokenise it, and return an instance of WordsCounted::Counter initialized with the tokens. The WordsCounted::Tokeniser and WordsCounted::Counter classes can be used alone, however.

API

WordsCounted

WordsCounted.count(input, options = {})

Tokenises input and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.count("Hello Beirut!")

Accepts two options: exclude and regexp. See Excluding tokens from the analyser and Passing in a custom regexp respectively.

WordsCounted.from_file(path, options = {})

Reads and tokenises a file, and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.from_file("hello_beirut.txt")

Accepts the same options as .count.

Tokeniser

The tokeniser allows you to tokenise text in a variety of ways. You can pass in your own rules for tokenisation, and apply a powerful filter with any combination of rules as long as they can boil down into a lambda.

Out of the box the tokeniser includes only alpha chars. Hyphenated tokens and tokens with apostrophes are considered a single token.

#tokenise([pattern: TOKEN_REGEXP, exclude: nil])

tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise

# With `exclude`
tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise(exclude: "hello")

# With `pattern`
tokeniser = WordsCounted::Tokeniser.new("I <3 Beirut!").tokenise(pattern: /[a-z]/i)

See Excluding tokens from the analyser and Passing in a custom regexp for more information.

Counter

The WordsCounted::Counter class allows you to collect various statistics from an array of tokens.

#token_count

Returns the token count of a given string.

counter.token_count #=> 15

#token_frequency

Returns a sorted (unstable) two-dimensional array where each element is a token and its frequency. The array is sorted by frequency in descending order.

counter.token_frequency

[
  ["the", 2],
  ["are", 2],
  ["we",  1],
  # ...
  ["all", 1]
]

#most_frequent_tokens

Returns a hash where each key-value pair is a token and its frequency.

counter.most_frequent_tokens

{ "are" => 2, "the" => 2 }

#token_lengths

Returns a sorted (unstable) two-dimentional array where each element contains a token and its length. The array is sorted by length in descending order.

counter.token_lengths

[
  ["looking", 7],
  ["gutter",  6],
  ["stars",   5],
  # ...
  ["in",      2]
]

#longest_tokens

Returns a hash where each key-value pair is a token and its length.

counter.longest_tokens

{ "looking" => 7 }

#token_density([ precision: 2 ])

Returns a sorted (unstable) two-dimentional array where each element contains a token and its density as a float, rounded to a precision of two. The array is sorted by density in descending order. It accepts a precision argument, which must be a float.

counter.token_density

[
  ["are",     0.13],
  ["the",     0.13],
  ["but",     0.07 ],
  # ...
  ["we",      0.07 ]
]

#char_count

Returns the char count of tokens.

counter.char_count #=> 76

#average_chars_per_token([ precision: 2 ])

Returns the average char count per token rounded to two decimal places. Accepts a precision argument which defaults to two. Precision must be a float.

counter.average_chars_per_token #=> 4

#uniq_token_count

Returns the number of unique tokens.

counter.uniq_token_count #=> 13

Excluding tokens from the tokeniser

You can exclude anything you want from the input by passing the exclude option. The exclude option accepts a variety of filters and is extremely flexible.

  1. A space-delimited string. The filter will normalise the string.
  2. A regular expression.
  3. A lambda.
  4. A symbol that names a predicate method. For example :odd?.
  5. An array of any combination of the above.
tokeniser =
  WordsCounted::Tokeniser.new(
    "Magnificent! That was magnificent, Trevor."
  )

# Using a string
tokeniser.tokenise(exclude: "was magnificent")
# => ["that", "trevor"]

# Using a regular expression
tokeniser.tokenise(exclude: /trevor/)
# => ["magnificent", "that", "was", "magnificent"]

# Using a lambda
tokeniser.tokenise(exclude: ->(t) { t.length < 4 })
# => ["magnificent", "that", "magnificent", "trevor"]

# Using symbol
tokeniser = WordsCounted::Tokeniser.new("Hello! محمد")
tokeniser.tokenise(exclude: :ascii_only?)
# => ["محمد"]

# Using an array
tokeniser = WordsCounted::Tokeniser.new(
  "Hello! اسماءنا هي محمد، كارولينا، سامي، وداني"
)
tokeniser.tokenise(
  exclude: [:ascii_only?, /محمد/, ->(t) { t.length > 6}, "و"]
)
# => ["هي", "سامي", "وداني"]

Passing in a custom regexp

The default regexp accounts for letters, hyphenated tokens, and apostrophes. This means twenty-one is treated as one token. So is Mohamad's.

/[\p{Alpha}\-']+/

You can pass your own criteria as a Ruby regular expression to split your string as desired.

For example, if you wanted to include numbers, you can override the regular expression:

counter = WordsCounted.count("Numbers 1, 2, and 3", pattern: /[\p{Alnum}\-']+/)
counter.tokens
#=> ["numbers", "1", "2", "and", "3"]

Opening and reading files

Use the from_file method to open files. from_file accepts the same options as .count. The file path can be a URL.

counter = WordsCounted.from_file("url/or/path/to/file.text")

Gotchas

A hyphen used in leu of an em or en dash will form part of the token. This affects the tokeniser algorithm.

counter = WordsCounted.count("How do you do?-you are well, I see.")
counter.token_frequency

[
  ["do",   2],
  ["how",  1],
  ["you",  1],
  ["-you", 1], # WTF, mate!
  ["are",  1],
  # ...
]

In this example -you and you are separate tokens. Also, the tokeniser does not include numbers by default. Remember that you can pass your own regular expression if the default behaviour does not fit your needs.

A note on case sensitivity

The program will normalise (downcase) all incoming strings for consistency and filters.

Roadmap

Ability to open URLs

def self.from_url
  # open url and send string here after removing html
end

Contributors

See contributors.

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

Author: abitdodgy
Source code: https://github.com/abitdodgy/words_counted
License: MIT license

#ruby  #ruby-on-rails 

Royce  Reinger

Royce Reinger

1658068560

WordsCounted: A Ruby Natural Language Processor

WordsCounted

We are all in the gutter, but some of us are looking at the stars.

-- Oscar Wilde

WordsCounted is a Ruby NLP (natural language processor). WordsCounted lets you implement powerful tokensation strategies with a very flexible tokeniser class.

Features

  • Out of the box, get the following data from any string or readable file, or URL:
    • Token count and unique token count
    • Token densities, frequencies, and lengths
    • Char count and average chars per token
    • The longest tokens and their lengths
    • The most frequent tokens and their frequencies.
  • A flexible way to exclude tokens from the tokeniser. You can pass a string, regexp, symbol, lambda, or an array of any combination of those types for powerful tokenisation strategies.
  • Pass your own regexp rules to the tokeniser if you prefer. The default regexp filters special characters but keeps hyphens and apostrophes. It also plays nicely with diacritics (UTF and unicode characters): Bayrūt is treated as ["Bayrūt"] and not ["Bayr", "ū", "t"], for example.
  • Opens and reads files. Pass in a file path or a url instead of a string.

Installation

Add this line to your application's Gemfile:

gem 'words_counted'

And then execute:

$ bundle

Or install it yourself as:

$ gem install words_counted

Usage

Pass in a string or a file path, and an optional filter and/or regexp.

counter = WordsCounted.count(
  "We are all in the gutter, but some of us are looking at the stars."
)

# Using a file
counter = WordsCounted.from_file("path/or/url/to/my/file.txt")

.count and .from_file are convenience methods that take an input, tokenise it, and return an instance of WordsCounted::Counter initialized with the tokens. The WordsCounted::Tokeniser and WordsCounted::Counter classes can be used alone, however.

API

WordsCounted

WordsCounted.count(input, options = {})

Tokenises input and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.count("Hello Beirut!")

Accepts two options: exclude and regexp. See Excluding tokens from the analyser and Passing in a custom regexp respectively.

WordsCounted.from_file(path, options = {})

Reads and tokenises a file, and initializes a WordsCounted::Counter object with the resulting tokens.

counter = WordsCounted.from_file("hello_beirut.txt")

Accepts the same options as .count.

Tokeniser

The tokeniser allows you to tokenise text in a variety of ways. You can pass in your own rules for tokenisation, and apply a powerful filter with any combination of rules as long as they can boil down into a lambda.

Out of the box the tokeniser includes only alpha chars. Hyphenated tokens and tokens with apostrophes are considered a single token.

#tokenise([pattern: TOKEN_REGEXP, exclude: nil])

tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise

# With `exclude`
tokeniser = WordsCounted::Tokeniser.new("Hello Beirut!").tokenise(exclude: "hello")

# With `pattern`
tokeniser = WordsCounted::Tokeniser.new("I <3 Beirut!").tokenise(pattern: /[a-z]/i)

See Excluding tokens from the analyser and Passing in a custom regexp for more information.

Counter

The WordsCounted::Counter class allows you to collect various statistics from an array of tokens.

#token_count

Returns the token count of a given string.

counter.token_count #=> 15

#token_frequency

Returns a sorted (unstable) two-dimensional array where each element is a token and its frequency. The array is sorted by frequency in descending order.

counter.token_frequency

[
  ["the", 2],
  ["are", 2],
  ["we",  1],
  # ...
  ["all", 1]
]

#most_frequent_tokens

Returns a hash where each key-value pair is a token and its frequency.

counter.most_frequent_tokens

{ "are" => 2, "the" => 2 }

#token_lengths

Returns a sorted (unstable) two-dimentional array where each element contains a token and its length. The array is sorted by length in descending order.

counter.token_lengths

[
  ["looking", 7],
  ["gutter",  6],
  ["stars",   5],
  # ...
  ["in",      2]
]

#longest_tokens

Returns a hash where each key-value pair is a token and its length.

counter.longest_tokens

{ "looking" => 7 }

#token_density([ precision: 2 ])

Returns a sorted (unstable) two-dimentional array where each element contains a token and its density as a float, rounded to a precision of two. The array is sorted by density in descending order. It accepts a precision argument, which must be a float.

counter.token_density

[
  ["are",     0.13],
  ["the",     0.13],
  ["but",     0.07 ],
  # ...
  ["we",      0.07 ]
]

#char_count

Returns the char count of tokens.

counter.char_count #=> 76

#average_chars_per_token([ precision: 2 ])

Returns the average char count per token rounded to two decimal places. Accepts a precision argument which defaults to two. Precision must be a float.

counter.average_chars_per_token #=> 4

#uniq_token_count

Returns the number of unique tokens.

counter.uniq_token_count #=> 13

Excluding tokens from the tokeniser

You can exclude anything you want from the input by passing the exclude option. The exclude option accepts a variety of filters and is extremely flexible.

  1. A space-delimited string. The filter will normalise the string.
  2. A regular expression.
  3. A lambda.
  4. A symbol that names a predicate method. For example :odd?.
  5. An array of any combination of the above.
tokeniser =
  WordsCounted::Tokeniser.new(
    "Magnificent! That was magnificent, Trevor."
  )

# Using a string
tokeniser.tokenise(exclude: "was magnificent")
# => ["that", "trevor"]

# Using a regular expression
tokeniser.tokenise(exclude: /trevor/)
# => ["magnificent", "that", "was", "magnificent"]

# Using a lambda
tokeniser.tokenise(exclude: ->(t) { t.length < 4 })
# => ["magnificent", "that", "magnificent", "trevor"]

# Using symbol
tokeniser = WordsCounted::Tokeniser.new("Hello! محمد")
tokeniser.tokenise(exclude: :ascii_only?)
# => ["محمد"]

# Using an array
tokeniser = WordsCounted::Tokeniser.new(
  "Hello! اسماءنا هي محمد، كارولينا، سامي، وداني"
)
tokeniser.tokenise(
  exclude: [:ascii_only?, /محمد/, ->(t) { t.length > 6}, "و"]
)
# => ["هي", "سامي", "وداني"]

Passing in a custom regexp

The default regexp accounts for letters, hyphenated tokens, and apostrophes. This means twenty-one is treated as one token. So is Mohamad's.

/[\p{Alpha}\-']+/

You can pass your own criteria as a Ruby regular expression to split your string as desired.

For example, if you wanted to include numbers, you can override the regular expression:

counter = WordsCounted.count("Numbers 1, 2, and 3", pattern: /[\p{Alnum}\-']+/)
counter.tokens
#=> ["numbers", "1", "2", "and", "3"]

Opening and reading files

Use the from_file method to open files. from_file accepts the same options as .count. The file path can be a URL.

counter = WordsCounted.from_file("url/or/path/to/file.text")

Gotchas

A hyphen used in leu of an em or en dash will form part of the token. This affects the tokeniser algorithm.

counter = WordsCounted.count("How do you do?-you are well, I see.")
counter.token_frequency

[
  ["do",   2],
  ["how",  1],
  ["you",  1],
  ["-you", 1], # WTF, mate!
  ["are",  1],
  # ...
]

In this example -you and you are separate tokens. Also, the tokeniser does not include numbers by default. Remember that you can pass your own regular expression if the default behaviour does not fit your needs.

A note on case sensitivity

The program will normalise (downcase) all incoming strings for consistency and filters.

Roadmap

Ability to open URLs

def self.from_url
  # open url and send string here after removing html
end

Are you using WordsCounted to do something interesting? Please tell me about it.

Gem Version 

RubyDoc documentation.

Demo

Visit this website for one example of what you can do with WordsCounted.


Contributors

See contributors.

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Add some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

Author: Abitdodgy
Source Code: https://github.com/abitdodgy/words_counted 
License: MIT license

#ruby #nlp 

walter geed

1605848956

Best Cryptocurrency Development Company | Cryptocurrency Software Solutions

Shamlatech is the Best Cryptocurrency Development Company with customized solutions for you.
Best Cryptocurrency Development Company to provide you a highly Customized Cryptocurrency Software development and marketing Solutions.

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aaron silva

aaron silva

1622197808

SafeMoon Clone | Create A DeFi Token Like SafeMoon | DeFi token like SafeMoon

SafeMoon is a decentralized finance (DeFi) token. This token consists of RFI tokenomics and auto-liquidity generating protocol. A DeFi token like SafeMoon has reached the mainstream standards under the Binance Smart Chain. Its success and popularity have been immense, thus, making the majority of the business firms adopt this style of cryptocurrency as an alternative.

A DeFi token like SafeMoon is almost similar to the other crypto-token, but the only difference being that it charges a 10% transaction fee from the users who sell their tokens, in which 5% of the fee is distributed to the remaining SafeMoon owners. This feature rewards the owners for holding onto their tokens.

Read More @ https://bit.ly/3oFbJoJ

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