Available via license: CC BY
Content may be subject to copyright.
CryptoKitties Transaction Network
Analysis: The Rise and Fall of the First
Blockchain Game Mania
Xin-Jian Jiang
1
and Xiao Fan Liu
2
*
1
School of Computer Science and Engineering, Southeast University, Nanjing, China,
2
Web Mining Laboratory, Department of
Media and Communication, City University of Hong Kong, Hong Kong, China
CryptoKitties was the first widely recognized blockchain game. Players could own, breed,
and trade kitties, which are the only prop in the game. The game gained explosive growth
upon its release but quickly collapsed in a short time. This study analyzes its entire player
activity history for the first time in literature and tries to find the reasons for the rise and fall of
this first blockchain game mania. First, we extracted the five million transaction records
among 100 thousand addresses involved in CryptoKitties in the past three years. Based on
the numbers of addresses involved in the game each day, we divide the game progress
into four stages: the primer, the rise, the fall, and the serenity. We construct a temporal kitty
ownership transfer network and analyze the varying network parameters in the four stages.
We find that a large number of players poured in during the 10th and 18th days since the
game release and quickly exited in the following month. Since then, a few big players have
gradually dominated the game, concentrating the game resources. Through further
analysis, we find that the main reason for the rapid increase in the game popularity
was the increase of public attention by media outlets, while the reasons for the rapid
decline in the game popularity include the oversupply of kitties, the decreasing of player
income, a widening gap between the rich and poor players, and the limitations of
blockchain systems. Based on these observations, we advise on the further
blockchain game design: (1) to finely control the production of props and avoid an
oversupply, (2) to balance the gaming cost and revenue and protect the enjoyment of
players, (3) to narrow down the gap between rich and poor and create an equal gaming
community, (4) to consider the limitations of blockchain systems in their game designs.
Keywords: cryptokitties, blockchain game, ethereum, transaction network, game design
1 INTRODUCTION
Blockchain, emerged as the underlying supporting technology for Bitcoin [1], is a distributed ledger
system providing non-tampering and traceability functionalities. Ethereum [2], also known as the
blockchain 2.0 platform, further adds supports for smart contracts, which are programs that can be
stored and executed on the blockchain system [3]. Developers can use smart contracts to create
various decentralized applications, especially games.
Blockchain games are considered to have unique advantages over traditional online games in that
their gaming data and logic are transparently stored and executed on blockchains [4]. These
advantages particularly suit games with in-game payment and chance mechanisms, e.g., gambling,
Edited by:
Hui-Jia Li,
Beijing University of Posts and
Telecommunications (BUPT), China
Reviewed by:
Xiapu Luo,
Hong Kong Polytechnic University,
Hong Kong
Jiajing Wu,
Sun Yat-Sen University, China
*Correspondence:
Xiao Fan Liu
xf.liu@cityu.edu.hk
Specialty section:
This article was submitted to
Social Physics,
a section of the journal
Frontiers in Physics
Received: 20 November 2020
Accepted: 21 January 2021
Published: 03 March 2021
Citation:
Jiang X-J and Liu XF (2021)
CryptoKitties Transaction Network
Analysis: The Rise and Fall of the First
Blockchain Game Mania.
Front. Phys. 9:631665.
doi: 10.3389/fphy.2021.631665
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316651
ORIGINAL RESEARCH
published: 03 March 2021
doi: 10.3389/fphy.2021.631665
which often suffered from trust issues in traditional online
environment. As a result, current designs of blockchain games
mainly revolve around the generation, ownership, and trading of
virtual assets [5].
Cryptokitties is a blockchain game released on Ethereum in
late November 2017. Players can own, trade, and create virtual
kitties, represented by non-fungible tokens meeting the ERC-721
token standard in the game. The attributes and transactions of
kitties are recorded in the Ethereum blockchain. Once released,
CryptoKitties soon gained massive popularity that its
transactions accounted for more than 10% of the entire
Ethereum traffic in early December 2017 [6].
Nonetheless, Min et al. [4] claimed that most of the current
blockchain games lack playability. Possible reasons include that
current blockchain platforms restrict developers from
implementing complex game functions, current developers are
paying insufficient attention to the players’gaming experience,
and lack a competitive market in the blockchain game industry.
Not surprisingly, the popularity of CryptoKitties only lasted for a
short period, too.
In this study, we aim to fully unveil the collective user
behaviors in the game and the reasons leading to the game’s
rapid rise and fall by analyzing blockchain transaction records.
Specifically, we first construct a kitty ownership transfer network
and investigate the network structural changes over time. Then,
we conjecture and verify the possible reasons for the rapid
changes in gaming popularity from four perspectives: the
supply and demand of kitties, the profitability in the game, the
inequality of players’wealth, and the limitations of blockchain
systems. Based on our observations, we pinpoint the deficiencies
in the design of CryptoKitties and provide suggestions for further
development of blockchain games.
Network analysis methods have been applied to
cryptocurrency transaction records in many previous works.
Chen et al. [7] constructed three graphs with ether transfer,
contract creation, and contract invocation, found a power-law
degree distribution, and revealed anomalies in these graphs.
Somin et al. [8] also found a power-law degree distribution in
the ERC20 token transfer network. Guo et al. [9] further revealed a
bow-tie structure in the Ethereum transaction network. Except for
the Ethereum blockchain, similar methods have also been used to
analyze transactions on other blockchains, such as EOSIO [10].
The rest of this paper is organized as follows. CryptoKitties’
gaming rules are introduced in Section 2.InSection 3,we
construct the kitty ownership transfer network and define
network structural properties. In Section 4, we divide the
progress of the game into four stages and examine the changes
of network parameters in different stages. We will discuss the
reasons for the rapid change in the popularity of CryptoKitties in
Section 5.Section 6 concludes the study and provides
suggestions for the further development of blockchain games.
2 GAMING RULES
As shown in Table 1, the CryptoKitties game has five smart
contracts: the Core contract, GeneScience contract, Offers
contract, SalesAuction contract, and SiringAuction contract.
The names of these contracts could be found on Etherscan
[11]. Based on these contracts, players can trade or transfer
kitties with other players and breed new kitties.
There are three ways to trade or transfer a kitty. (1) Using
the SalesAuction contract. The seller lists a kitty for sale with
an initial price, a final price, and a price change period to the
SalesAuction contract. The initial price is usually higher than
the final price. After the auction begins, the kitty price will
change linearly from the initial price to the final price at a
constant rate during the price change period. The price will
not change after this period. Unless bid by a buyer or canceled
by the seller, the kitty will remain in the SalesAuction
contract. Upon receiving a bid, the SalesAuction contract
will send the kitty to the buyer and transfer the payment to
the seller. The game publisher also sells 0-generation kitties to
players in this way. (2) Using the Core contract. A player can
either call the transfer function to transfer his kitty to another
player or the approve function to allow other players to
transfer his kitty. Authorized players can call transfer from
function to transfer other players’kitties. Transferring a kitty
in this way does not necessarily mean that the player is trading
the kitty but can also be sending a kitty as a gift to a friend. (3)
Using the Offers contract. In this way, the buyer initiates a
request to the seller and sends the purchase fee to the Offers
contract. If the seller accepts the request, the Offers contract
will transfer the kitty to the buyer’saddressandsendthe
purchase fee to the seller.
When trading kitties through the SalesAuction, the game
publisher charges the sellers for 3.75% of the dealing price as
a handling fee. Same rate of dealing price will be charged to the
buyers using the Offers contracts. When calling any function in
each contract, the players also need to pay gas fees to Ethereum
miners through their Ethereum wallet. The gas fee is usually
between 0.0001eth and 0.01eth.
There are two ways to breed a new kitty. (1) A player selects
two of his own kitties as parameters and call the breed With Auto
function in the Core contract with a breeding fee. After this
operation, the mother kitties (can be arbitrarily chosen between
the two) will become pregnant for a period. After this period, a
player, also called the midwife, will call the give birth function in
the Core contract to give birth to the new kitty. The newborn kitty
will be transferred to the owner of the mother kitty. The breeding
fee will be compensated to the midwife for their Ethereum gas fees
paid. (2) A player breeds with one of his own kitties and another
rented from the Siring Auction contract, which lists a number of
kitties owned by the lenders. A midwife is also needed in this case.
TABLE 1 | CryptoKitties’s smart contracts.
Contract name Main functions
Core Record all kitties’attributes and owner information
SalesAuction As an intermediary to help player trade kitties
Offers As an intermediary to help player trade kitties
SiringAuction As an intermediary to help player rent kitties
GeneScience Calculate the genes of newborn kitties
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316652
Jiang and Liu CryptoKitties Transaction Network Analysis
When a kitty is rented out through the Siring Auction contract,
the game publisher will charge the lender 3.75% of the rent as a
handling fee.
The breeding fee varied over time (see Figure 1). It was set to
0.002eth at the game’s release. However, due to the congestion of
the Ethereum network resulting from the gaming transactions,
the gas fee was raised. The game publisher increased the breeding
fee to 0.015eth and later adjusted it to 0.008eth. Such adjustment
happened several times afterward, but despite that, the breeding
fee has been stable at 0.008eth.
3 DATA AND METHODS
3.1 Blockchain Transactions
We synchronized an Ethereum parity client in full mode and used
the eth_getLogs method to extract the transactions in
CryptoKitties. The transactions span from November 23, 2017,
to May 19, 2020. The data involved 1,923,901 kitties, 104,517
addresses, and 5,173,521 transfer records. There are nine types of
transactions (see Table 2) related to the movements of kitties,
including the trading, transferring, and the new birth of kitties.
Consider participation rate as the ratio of the number of
addresses that take part in a specific activity to the number of
all addresses in CryptoKitties, buying kitties through the
SalesAuction contract has the highest participation rate
(84.6%), indicating that most players would buy at least one
kitty from the official marketplace. Participation rates are also
high for breeding kitty (64.9%) and selling kitty through the
SalesAuction contract (51.8%). Players showed low interest in
lending (38.1%) and renting kitties (26.6%). Only a very small
number of players (less than 1%) traded kitties through the Offers
contract.
3.2 Constructing Ownership Transfer
Network of Kitties
The actual ownership of the kitties only changes when (1) the
sales auction on the SalesAuction contract is fulfilled, (2) the
trading through the Offers contract is fulfilled, and (3) kitties are
transferred directly using functions in the Core contract.
Therefore, We construct the kitty ownership transfer network
G(V,E), where Vis the set of addresses belong to kitty owners,
including the game publisher and players, who have the actual
ownership of kitties, and Eis the set of directed edges representing
the actual ownership changes. The directed edges e(u,v,t)are
temporal, where urepresents the address of kitty’s previous
owner, vrepresents the address of kitty’s new owner, and t
represents the time when the ownership change occurred. The
network contains 104,514 nodes and 1,304,525 edges. We further
use three days as the window size and construct a series of
temporal networks G(G1,G2,...), where Gtis the network
in time window t.
3.3 Network Structural Properties
We use the average degree, non-zero in-/out-degree ratio, Gini
coefficient of in-, out-, and total degrees, average clustering
coefficient, density, reciprocity, and assortativity to describe
the structural properties of the network.
The average degree k2M/Nrepresents the average number
of kitties transferred in and out of the addresses, where Mis the
number of edges and Nis the number of nodes in the temporal
network.
The non-zero in-/out-degree ratio αNout >0/Nin >0is defined
as the ratio of the number of nodes with an out-degree greater
than zero (Nout >0) to those with an in-degree greater than zero
FIGURE 1 | Changes of the breeding fee.
TABLE 2 | Nine types of transactions related to the movements of kitties.
Transaction type From To Amount
Kitty birth 0x Owner 1,923,901
Listing on the SalesAuction contract Seller SalesAuction 1,126,964
Cancel listing on the SalesAuction
contract
SalesAuction Seller 241,614
Buying from the SalesAuction
contract
SalesAuction Buyer 668,981
Transferring through the core
contract
Sender Reviver 633,208
Trading through the offers contract Seller Buyer 2,336
Listing on the SiringAuction contract Lender SiringAuction 326,553
Cancel listing on the SiringAuction
contract
SiringAuction Lender 92,507
Rental finished SiringAuction Lender 157,457
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316653
Jiang and Liu CryptoKitties Transaction Network Analysis
(Nin >0) in the temporal network. It can also be considered as the
ratio of the number of sellers to buyers in the game.
The Gini coefficient Gkof the total degree kof all nodes in the
temporal network reflects the gap between the players’activeness
in the number of kitties transferred in and out of the address, i.e.,
Gk1
NN+1−2N
i1(N+1−i)ki
N
i1ki,
where kiis the degree of node iindexed in non-decreasing order
(ki≤ki+1) and Nis the number of nodes in the network. The Gini
coefficients for the in-degrees Gkin and out-degrees Gkout of all
nodes can be defined likewise.
The average clustering coefficient cis used to measure the
clustering degree of the network, which is defined as
c1
N
v∈V
Tv
kv(kv−1)−2kr
v
,
where Tvis the number of directed triangles passing through the
node v,kvis the degree of node v, and kr
vis the number of
bidirectional edges of node v. Multiple edges between uand vare
considered as one even with the same tin this case. High average
clustering coefficient means that players interact closely with
other players.
Network density dM/(N(N−1)) describes the portion of
the potential connections in the network that are actual
connections. Again, multiple edges between uand vare
considered as one even with the same tin this case.
The reciprocity ρ2Mu/Mdescribes the ratio of the number
of edges pointing in both directions to the total number of edges
in the network, where Muis the number of undirected edges in
the network. High reciprocity means that the relationship
between addresses is relatively strong, and the owners of
these addresses are likely to know each other. Multiple edges
between uand vare considered as one even with the same tin
this case.
The degree assortativity coefficient rmeasures the similarity of
connections in the network with respect to the node degree:
rijAij −kikj2Mkikj
ijkiδij −kikj2Mkikj
,
where Aij is an element in the adjacency matrix, kiand kjare the
degrees of node iand j, and δij is the Kronecker function. The
direction of edge is ignored and multiple edges are considered in
the calculation.
4 COLLECTIVE BEHAVIORS OF
CRYPTOKITTIES PLAYERS
4.1 The Four Stages of Game Progress
Using the numbers of daily addresses related to CryptoKitties
transactions, the game can be divided into four stages: the primer,
the rise, the fall, and the serenity, as shown in Figure 2.
1. The primer: The game was released on November 23, 2017.
There were not many players before December 2, 2017.
2. The rise: A large number of players entered the game since
December 2, 2017. The game popularity rapidly increased
before reaching a peak on December 10.
3. The fall: Since then, the popularity has dropped sharply. At the
beginning of 2018, the game’s popularity is less than 10% of
its peak.
4. The serenity: After January 15, 2018, the popularity stabilized
into a long-term slow downward trend. Figure 3 shows four
snapshots of the network in each of the stages. The network
size shrinks apparently over time.
4.2 Evolution of the Network Structure
The evolution of network structural properties in the four stages
are shown in Figure 4. In the first stage, the Gini coefficient of
out-degrees decreased suddenly. This is because almost all 0-
generation kitties were transferred from the game publisher’s
addresses to the players in the first few days. Soon after that,
players began to breed new kitties and sell them to each other. The
decreases in average degree, network density, and average
clustering coefficient result from early players entering the
game and expanding the network. Meanwhile, the assortativity
coefficient stayed negative because low-degree players tended to
trade with high-degree players, who are the game publisher.
In the second stage, the network density stayed low due to the
large number of players entering the game. The degree
FIGURE 2 | Four stages of the game. The three dotted lines correspond to December 1, 2017, December 10, 2017, and January 15, 2018, respectively.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316654
Jiang and Liu CryptoKitties Transaction Network Analysis
assortativity coefficient increased to zero, meaning that low-
activity players tended to transfer kitties among themselves
rather than trading with high-activity players.
In the third stage, the non-zero in-/out-degree ratio
maintained an upward trend, indicating that the ratio of
sellers to buyers was increasing, and market competition was
intensifying. The Gini coefficient of out-degrees decreased gently,
indicating that even the seller/buyer ratio increased, the gap
between sales volume among sellers was narrowing. However,
in-degrees’Gini coefficient went up suddenly. The anomalous
data point around December 23, 2017, was caused by an
exceptionally large number of transactions made by a handful
of addresses.
In the fourth stage, the increasing average degree and
reciprocity indicate that the players left in the games were
actively trading with each other. The Gini coefficients all
maintained an upward trend, indicating a large gap forming in
these players: some big players were gradually dominating
the game.
Note that the average degree, Gini coefficients, and reciprocity
suddenly increased in June 2019. We found that they were caused
by the launch of Wrapped Cryptokitties (WCK), which is an
ERC-20 token contract, enabling players to exchange unwanted
ERC-721 kitties for WCK and use WCK to exchange other kitties.
The replacement of a large number of ERC-721 kitties with WCK
resulted in a sudden fluctuation in the network structure.
4.3 Changes in the Kitty Ownership
Transferring Methods
There are three ways to transfer the ownership of kitties: through
the SalesAuction, Offers, or Core contracts. The changes in the
proportions of the three methods over time are shown in
Figure 5. In the early days of the game, the ownership
transfer of kitties was mainly realized through the
SalesAuction contract. Later, the proportion of transferring
kitties with the method in Core contract gradually increased.
After April 2019, this method had become the main way of
transferring kitty ownerships. The number of kitties transferred
through the Offers contract was always small.
Cost was the main reason for this change. Players tend to
transfer kitties at a lower cost. When buying and selling kitties
through the SalesAuction and Offers contracts, players need to
pay a transaction fee to the game publisher, usually 3.75% of the
transaction amount. Using the transfer method in the Core
contract, in contrast, only requires a gas fee payment.
FIGURE 3 | Visualizations of typical networks in every stage. Nodes in the network are filtered by out-degree. (A) There aren’t many early players in stage 1. (B) The
network contains a large number of nodes in stage 2. (C) The network shrinks in stage 3. (D) Only long-term players are left in stage 4.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316655
Jiang and Liu CryptoKitties Transaction Network Analysis
Therefore, some third-party trading platforms emerged to help
players trade kitties, charging fewer transaction fees. For example,
the transaction fee charged by the OpenSea trading platform is
only 2.5%.
5 REASONS FOR THE RISE AND FALL OF
CRYPTOKITTIES
5.1 Reasons for the Explosive Growth of
Game Popularity
On December 2, 2017, the kitty with ID 1 was sold for 247eth,
i.e., more than US $100,000 [12]. This message spread quickly on
the Internet, generating a large amount of attentions. Figure 6
shows the Google trend index of CryptoKitties and number of
daily addresses related to CryptoKitties transactions. Kitties
traded at extremely high prices will undoubtedly attract media
attention and bring many new players to the game. The increased
attention from Internet users eventually led to the explosive
growth of the game’s popularity. We cannot rule out the
possibility that the game publisher deliberately made the news
that a special kitty has being sold at an extremely high price. In
fact, almost all transactions with an amount greater than 100eth
occurred in early December 2017, which corresponds precisely to
the rise stage of the game. Nonetheless, despite of the cause, media
exposure had indeed increased the game popularity significantly.
G
A
B
C
D
E
F
FIGURE 4 | Evolution of the network structural properties over time. (A) The average degree, (B) the non-zero in-/out-degree ratio, (C) the Gini coefficients of in-,
out-, and total degrees, (D) the average clustering coefficient, (E) network density, (F) reciprocity, and (G) assortativity. Dotted lines separates the four stages. The labels
on the x-axis represent the middle date of time windows. The x-axis are re-scaled to better illustrate the parameter dynamics in stages 1, 2 and 3.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316656
Jiang and Liu CryptoKitties Transaction Network Analysis
Cryptocurrencies, such as Bitcoin, show a positive correlation
between their prices and the sizes of the user groups [13–15]. The
kitties in the game are ERC-721 token, and therefore, the same
rule applies. On the one hand, the expansion of the player
community has increased the demand for kitty tokens and
promoted the rise of kitty price. On the other hand, the
increase in kitty price attracted more players to join the
community. Eventually, the entry of a large number of players
into the game has led to a surge in demand for kitties, hence the
kitty price (see Figure 7). The mean price of kitties in each day is
significantly higher than the median price because a small
number of kitties were sold at significantly higher prices than
average.
5.2 Reasons for the Rapid Fading of Game
Popularity
The rapid growth of game popularity only lasted less than ten
days. Since then, the number of players has dropped sharply. Lee
et al. [16] noted that users’playing behaviors in CryptoKitties are
affected by speculative and enjoyable factors. Here, we propose
four specific reasons that could account for the rapid decline in
game popularity: the out-of-balance of the supply and demand of
kitties; the loss of profit in kitty trading; the increasing gap
between the rich and poor players, and the limitations of
blockchain systems.
5.2.1 The out of Supply and Demand Balance
The large number of players poured in during the explosive
growth stage bred a large number of kitties in a very short time.
Since December 4, 2017, the number of new kitty listings has
significantly exceeded the number of kitties sold every day,
resulting in a rapid increase in the number of kitties left on
sale, i.e., stock inventory (see Figure 8A). The kitty market has
become a buyer’s market, and the competition has intensified.
The ratio of a successful sale for kitties listed on each day also
decreased (see Figure 8B), and the turnover time, i.e., the average
time interval between kitty listing and trade closing becomes
longer (see Figure 8C).
5.2.2 The Loss of Profit in Kitty Trading
Buchholz et al. [17] pointed out that the value of
cryptocurrencies has no benchmark but purely depend on
the supply and demand in the market. As the supply of
kitties significantly overwhelmed the demand, the price of
kitties dropped significantly. Profitisanimportant
motivation to encourage the players to stay in the game. If
their revenue from selling kitties becomes lower than the costs,
the players’enthusiasm will decline or even disappear.
FIGURE 5 | The change in proportion of three methods to transfer the kitties.
FIGURE 6 | Google Trends of CryptoKitties and the numbers of daily
active addresses.
FIGURE 7 | Mean and median prices of the kitties sold in each day.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316657
Jiang and Liu CryptoKitties Transaction Network Analysis
Teoretically, suppose a player uses two of his own kitties to
breed a new kitty and sell it at the median kitty price (excluding
the 0-generation kitties) through the SalesAuction contract on the
same day. The average cost of breeding and selling a kitty in one
day can be written as
cfbreed +gbreed +gsell,
where fbreed is the average breeding fee, gbreed is the average gas fee
for kitty breeding, and gsell is the average gas fee to sell a kitty
through SalesAuction contract on a particular day. The profitofa
kitty sale on the same day can be written as
p0.9625 ×vmedian −c,
where vmedian is the median price of kitties (excluding 0-
generation kitties) sold on that day. The seller can only receive
96.25% of the dealing price after deducting the 3.75% handling fee
received by the game publisher.
Figure 9A shows that the cost break-down for breeding and
selling increased sharply in stage 2. Among all the costs, the
breeding fee is the highest, followed by the miner’s fee for the
selling operation, and the miner’s fee for the breeding operation is
the lowest. Figure 9B shows that starting from December 13,
2017, the average profit for a player to breed and sell a kitty
FIGURE 8 | The supply and demand of kitties in the market. (A) The numbers of new kitty listings, kitties sold, and kitties on sale in the market every day. (B) The
ratio of successful sale for kitties listed on each day. (C) Turnover time, i.e., the average time interval between kitty listing and trade closing for kitties listed on each day.
Dotted lines separates the stage 1, 2 and 3.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316658
Jiang and Liu CryptoKitties Transaction Network Analysis
became negative, indicating that the player may lose money when
playing the game.
The actual in-game breeding and sale may not happen on the
same day. For every kitty sold, the seller’s actual profit can be
evaluated by the difference between the breeding or acquisition
cost and selling revenue. Here, we also estimate the actual profitof
kitties sold each day. For the kitty sold for the first time, the
seller’s profit can be written as
p10.9625 ×v−fbreed −gbreed −gsell −r−grent,
where vis the price at which the kitty is sold, fbreed is the breeding
fee, gbreed is the gas fee for kitty breeding, and gsell is the gas fee to
sell the kitty. If the player rents another player’s kitty, he has to
pay the rent rand gas fee grent. The seller can only receive 96.25%
of the dealing price after deducting the 3.75% handling fee for the
game publisher. For the kitties that are bought from others and
resold, the seller’s profit can be written as
p20.9625 ×vsold −vpurchase −gpurchase −glisting,
where vsold is the sold price, vpurchase is the purchase price, gpurchase
and glisting are the gas fees paid in purchasing and selling the kitty.
The seller can only receive 96.25% of the dealing price after
deducting the 3.75% handling fee for the game publisher.
Figure 10 shows the probability of generating a positive profit
by selling kitties each day. After December 6, 2017, this
probability for kitty resales became less than 50%. After
December 13, 2017, this probability for selling self-bred kitties
became less than 50%. Whether the player sells kitties bred by self
or previously purchased, there is a great chance of losing money.
5.2.3 The Increasing Gap Between the Rich and Poor
Players receive revenue from selling and lending kitties. In the
first stage of the game, the Gini coefficient of daily revenue from
selling and leasing increased significantly (see Figure 11A), and
that of the cumulative revenue for all the addresses also
increased significantly (see Figure 11B). After entering the
third stage, although the Gini coefficient of the revenue
earned by players from selling and renting fluctuated, they all
remained at a relatively high level (greater than 0.6). The Gini
coefficient of accumulated revenue stayed at a high level (greater
than 0.8). Since 0-generation kitties were mainly sold by game
publisher, these sales were not considered when counting the
revenue of players. Our results show that the gap between the
rich and poor in the game expanded. A few players earned most
of the money from the game, while most can only get very little
income, if any. The increasing gap in the revenue has caused
most players’gaming experience to deteriorate, and they
gradually withdrew from the game.
Not only the revenues, kitty ownerships were also gradually
concentrated to a few players. The Gini coefficient of the number of
kitties owned by all addresses at each stage is shown in Figure 12.
When counting the number of kitties belong to an address, unsold
kitties in the SalesAuction contract belong to the seller, and
unrented kitties in the SiringAuction contract belong to the
lender. In the first and second stages, many new players entered
the game, all making purchasing, and the Gini coefficient gradually
decreased. However, as the number of new players decreased and
existing players quit, the Gini coefficient rose in the third stage and
kept risingin the fourth stage. As of April 2020, the Gini coefficient
of kitties with addresses has exceeded 0.8. At this time, the
resources in CryptoKitties became highly concentrated.
5.2.4 Limitations of Blockchain Systems
The cost of performing operations on a public blockchain
system is highly volatile due to the unstable price of
FIGURE 9 | The loss of profit in kitty sales. (A) The average breeding fee, gas fee for breeding, and gas fee for selling a kitty throu gh SalesAuction contract on each
day. (B) The revenue (median price of kitties), cost, and profit for breeding and selling a kitty on each day. Dotted lines separates the stage 1, 2 and 3.
FIGURE 10 | The probability of generating positive profit in selling a kitty
each day. Dotted lines separates the stage 1, 2 and 3.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 6316659
Jiang and Liu CryptoKitties Transaction Network Analysis
cryptocurrencies, resulting in it difficult to control the cost of
the applications deployed on the blockchain. As CryptoKitties
was deployed on Ethereum, the cost of playing the game
(including the costs of buying, breeding, and renting
kitties, as well as the fees paid to Ethereum miners) has
risen significantly due to the rapid rise of Ether price in
the third stage. Ether price increased from US $451 on
December 10, 2017, to US $1,322 on January 10, 2018 (see
Figure 13), resulting in a significant increase in the cost of
playing the game, raising the bars for new players entering
the game.
In addition to the cryptocurrency price, other potential
limitations of blockchain systems include the unnecessary gas
cost by poorly designed smart contracts and the low system
throughput (measured in transaction per second, TPS).
Under-optimized smart contracts will consume more gas
than necessary [18], making it more expensive for users to
play games. Chen et al. [19,20] studied the gas cost
mechanismofEthereumandproposedawaytooptimize
smart contracts through analyzing bytecodes, potentially
reducing the gaming costs. The low throughput of
Ethereum [21] has rendered that concurrent operations by
many users are not feasible. Once too many players have
joinedthegame,thetimeneededtovalidateoperationsinthe
game takes too long, therefore sabotaging the players' gaming
experiences.
6 CONCLUSION
This paper is the first to fully unveil the user activities in the
once most popular blockchain game CryptoKitties and
AB
FIGURE 11 | Gini coefficients of (A) daily selling and lending revenue and (B) the accumulate revenue from kitty sale and renting for all the addresses. Dotted lines
separates the stage 1, 2 and 3.
FIGURE 12 | The Gini coefficient of kitties owned by all addresses. Dotted lines separates the four stages. The x-axis are re-scaled to better illustrate the parameter
dynamics in stages 1, 2 and 3.
FIGURE 13 | The Ether price. Dotted lines separates the stage 1, 2
and 3.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 63166510
Jiang and Liu CryptoKitties Transaction Network Analysis
identify the reasons for its rise and fall. Based on the number
of addresses associated with the game every day, we divide the
process of CryptoKitties into four stages: the primer, the rise,
the fall, and the serenity. We extracted all the five million
kitty transactions from the Ethereum blockchain and
constructed the kitty ownership transfer network for
characterizing the user behaviors. We found that a large
number of players flooded in the game in the early days
but quickly withdrew later, and a few big players gradually
took control of the game.
We found that the public attention drew by the message that a
special kitty was sold at an extremely high price eventually led to
the explosive growth of game popularity. For the rapid decline of
the popularity, reasons including 1) the oversupply of game
props, i.e., the kitties, 2) the loss of profit in the game prop
trading, 3) the increasing gap between the wealth distribution
among the players, and 4) the limitations of blockchain are
accounted for.
Drawing from these observations, we advise on the designing
of future blockchain games as follows.
1. Design a reasonable prop output mechanism to keep a balance
between supply and demand.
2. Provide a mechanism for adjusting player income to prevent
players losing money in prop trading with a high
probability.
3. Design a mechanism to narrow down the gap between the rich
and poor and prevent the revenue from being gained by only a
few players.
4. To fully consider the limitations of blockchain systems in the
game design.
DATA AVAILABILITY STATEMENT
Publicly available datasets were analyzed in this study. This
data can be found here: https://github.com/jiangxjcn/
Cryptokitties-analysis.git.
AUTHOR CONTRIBUTIONS
Both authors designed the study and wrote the paper. XJJ
conducted data analysis.
FUNDING
This work is supported by CityU Start-up Grant for New Faculty
(No. 7200649) and CityU Strategic Research Grant (No.
11503620).
ACKNOWLEDGMENTS
We thank Si-Hao Liu and Ying-Hao Zhang for their suggestions
on the revision of this article.
REFERENCES
1. Nakamoto S. Bitcoin: A peer-to-peer electronic cash system (2008).
2. Buterin V. Ethereum white paper: a next generation smart contract &
decentralized application platform (2014).
3. Mohanta BK, Panda SS, Jena D. An overview of smart contract and use cases in
blockchain technology. In: 2018 9th International conference on computing,
communication and networking technologies (INCCCNT); 2018 July 10–12;
Bangalore, India. NEW YORK: IEEE (2018), 1–4.
4. Min T, Wang H, Guo Y, Cai W. Blockchain games: a survey. In: 2019 IEEE Conference
on Games (CoG); 2019 August 20–23; London, United Kingdom. NEW YORK: IEEE
(2019). p. 1–8.
5. Scholten OJ, Hughes NGJ, Deterding S, Drachen A, Walker JA, Zendle D. Ethereum
crypto-games: mechanics, prevalence, and gambling similarities. In: Chi Play’19:
Proceedings of the Annual Symposium on Computer-Human Interaction in Play;
2019 October 17; Barcelona, Spain. New York: ACM (2019) 379–89.
6. Cryptokitties craze slows down transactions on ethereum (2017). Available from:
http://www.bbc.com/news/technology-42237162 (Accessed December 5, 2017).
7. ChenT,ZhuY,LiZ,ChenJ,LiX,LuoX,etal.Understandingethereumviagraph
analysis. In: IEEE INFOCOM ’18 conference on computer communications; 2018
April 16–19; Honolulu, HI, USA. NEW YORK: IEEE (2018a). p. 1484–92.
8. Somin S, Gordon G, Altshuler Y. Social signals in the ethereum trading network
(2018). p. 12097. Available from: arXiv:1805.12097.
9. Guo D, Dong J, Wang K. Graph structure and statistical properties of ethereum
transaction relationships. Inf Sci (2019) 492:58–71. doi:10.1016/j.ins.2019.04.013
10. Huang Y, Wang H, Wu L, Tyson G, Luo X, Zhang R, et al. Understanding
(Mis)Behavior on the EOSIO blockchain. Proc ACM Meas Anal Comput Syst
(2020) 4(2):1–28. doi:10.1145/3392155
11. Etherscan. The ethereum block explorer (2017). Available from: https://etherscan.io/
(Accessed May 19, 2020).
12. Tepper F. People have spent over $1 m buying virtual cats on the ethereum
blockchain (2017). Available from: https://techcrunch.com/2017/12/03/
people-have-spent-over-1m-buying-virtual-cats-on-the-ethereum-blockchain/
(Accessed December 4, 2017).
13. Baumann A, Fabian B, Lischke M. Exploring the bitcoin network. In: 10th
International Conference on Web Information Systems and Technologies
volume 2: WEBIST ’14; 2014 Apr 3–5; Barcelona, Spain. Setúbal, Portugal:
SciTePress (2014), 369–74.
14. Sorgente M, Cibils C. The reaction of a network: exploring the relationship
between the bitcoin network structure and the bitcoin price (2014). Available
from: http://snap.stanford.edu/class/cs224w-2014/projects/cs224w-27-final.
pdf (Accessed December 10, 2014).
15. Szücs I, Kiss A. Quantitative analysis of bitcoin exchange rate and transactional
network properties. In: 9th International Conference on Applied Informatics;
2014 Jan 29–Feb 1; Eger, Hungary. (2015), vol. 1, 201–11.
16. Lee J, Yoo B, Jang M. Is a blockchain-based game a game for fun, or is it a tool for
speculation? an empirical analysis of player behavior in crypokitties. In: Xu JJ, Zhu B,
Liu X, Shaw MJ, Zhang H, Fan M, editors. The ecosystem of e-business: technologies,
stakeholders, and connections. WEB 2018. Lecture Notes in Business Information
Processing. vol. 357. Cham, Switzerland: Springer International Publishing (2018). p.
141–8.
17. Buchholz M, Delaney J, Warren J, Parker J. Bits and bets, information,
price volatility, and demand for bitcoin (2012). Available from: https://
www.reed.edu/economics/parker/s12/312/finalproj/Bitcoin.pdf (Accessed
May 19, 2020).
18. Chen T, Li X, Luo X, Zhang X. Under-optimized smart contracts devour your
money. In: 2017 IEEE 24th international conference on software analysis,
evolution and reengineering (SANER); 2017 Feb 20–24; Klagenfurt, Austria.
NEW YORK: IEEE (2017). p. 442–6.
19. Chen T, Li Z, Zhou H, Chen J, Luo X, Li X, et al. ving money in Towards saving
money in using smart contracts. In: 2018 IEEE/ACM 40th international
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 63166511
Jiang and Liu CryptoKitties Transaction Network Analysis
conference on software engineering: new ideas and emerging technologies
results (ICSE-NIER); 2018 May 27–June 3; Gothenburg, Sweden. NEW YORK:
IEEE (2018b). p. 81–4.
20. Chen T, Li X, Wang Y,Chen J, Li Z, Luo X, et al. Anadaptive gas cost mechanism
for ethereum to defend against under-priced DoS attacks. In: Liu J, Samarati P,
editors. International conference on information security practice and
experience; 2017 December 13–15; Melbourne, Australia. Cham, Switzerland:
Springer (2017b). p. 3–24.
21. Tang H, Shi Y, Dong P. Public blockchain evaluation using entropy and topsis.
Expert Syst Appl (2019) 117:204–10. doi:10.1016/j.eswa.2018.09.048
Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
Copyright © 2021 Jiang and Liu. This is an open-access article distributed under the
terms of the Creative Commons Attribution License (CC BY). The use, distribution
or reproduction in other forums is permitted, provided the original author(s) and the
copyright owner(s) are credited and that the original publication in this journal is
cited, in accordance with accepted academic practice. No use, distribution or
reproduction is permitted which does not comply with these terms.
Frontiers in Physics | www.frontiersin.org March 2021 | Volume 9 | Article 63166512
Jiang and Liu CryptoKitties Transaction Network Analysis
