A Survey of Research in Real-Money Trading (RMT) in Virtual World

Nazir, Mohamed; Lui, Carrie Siu Man

doi:10.4018/ijvcsn.2017010103

Cited by 3 publications

(2 citation statements)

References 61 publications

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“…Users can often encounter feelings of uncertainty, expected regret, or too little trust during a transaction [18]. RMT itself is sometimes hidden in normal activities, such as sending gifts through a game's friends system [1]. This makes user tracking very limited [38].…”

Section: Challenges In E-currenciesmentioning

confidence: 99%

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Consumers’ Adoption and Use of E-Currencies in Virtual Markets in the Context of an Online Game

Gawron

Strzelecki

2021

JTAER

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Virtual worlds have created unique economies whose outcome is e-currencies, which link the electronic universe and reality. This article aims to examine how perceived usefulness, perceived ease of use, perceived risks, and perceived trust significantly impact consumers’ virtual currencies’ behaviour. The study tested and used an adapted TAM model in the context of virtual currencies using structural equation modelling. The partial least square method of structural equation modelling is employed to test the proposed research model. The study utilises an online survey to obtain data from 205 virtual currency consumers. The data set was analysed using SmartPLS 3 software. The results showed that the best predictor of consumers’ intention to use virtual currencies is perceived usefulness, followed by perceived ease of use. Perceived trust predicts consumers’ perceived usefulness and perceived ease of use. These findings reveal that virtual currencies are seen as useful and easy to use. Consumers trust them enough but notice the risks they carry. They can also accept problems associated with them when it comes to their intention to use them.

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Section: Challenges In E-currenciesmentioning

confidence: 99%

“…Real institutions recognise their role and importance. The amount of money invested in virtual worlds is enormous [1]. The market importance is acknowledgeable for all stakeholders, such as countries, producers, or consumers.…”

Section: Introductionmentioning

confidence: 99%

Consumers’ Adoption and Use of E-Currencies in Virtual Markets in the Context of an Online Game

Gawron

Strzelecki

2021

JTAER

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PU-Detector: A PU Learning-based Framework for Real Money Trading Detection in MMORPG

Wang,

Zhao,

Zhao

et al. 2024

ACM Trans. Knowl. Discov. Data

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Massively multiplayer online role-playing game (MMORPG) has been becoming one of the most popular and exciting online games. In recent years, a cheating phenomenon called real money trading (RMT) has arisen and damaged the fantasy world in many ways. RMT is the sale of in-game items, currency, or even characters to earn real money, breaking the balance of the game economy ecosystem and damaging the game experience. Therefore, some studies have emerged to address the problem of RMT detection. However, they cannot well handle the label uncertainty problem in practice where there are only labeled RMT samples (positive samples), and unlabeled samples which could either be RMT samples or normal transactions (negative samples). Meanwhile, the trading relationship between RMTers is modeled in a simple way, leading to some normal transactions being falsely classified as RMT. In this paper, we propose PU-Detector, a novel framework based on PU learning (learning from positive and unlabeled data) for RMT detection, considering the fact that there are only labeled RMT samples and other unlabeled transactions. We first automatically estimate the likelihood of one transaction being RMT by developing an improved PU learning method and proposing an assessment rule. Sequentially, we use the estimated likelihood as edge weight to construct a trading graph to learn trader representation. Then, with the trader representations and basic trading features, we detect RMT samples by the improved PU learning method. PU-Detector is evaluated on a large-scale real world dataset consisting of 33,809,956 transaction logs generated by 43,217 unique players. Compared with other approaches, it achieves the state-of-the-art performance and demonstrates its advantages in detecting underlying RMT samples.

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Factoring economic biases out of tokenomics

Baldo,

Migliardi

2023

2023 46th MIPRO ICT and Electronics Convention (MIPRO)

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A Survey of Research in Real-Money Trading (RMT) in Virtual World

Cited by 3 publications

References 61 publications

Consumers’ Adoption and Use of E-Currencies in Virtual Markets in the Context of an Online Game

Consumers’ Adoption and Use of E-Currencies in Virtual Markets in the Context of an Online Game

PU-Detector: A PU Learning-based Framework for Real Money Trading Detection in MMORPG

Factoring economic biases out of tokenomics

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