Online game involves a very large number of users who are interconnected and interact with each other via the Internet. We studied the characteristics of exchanging virtual goods with real money through processes called "real money trading (RMT)." This exchange might influence online game user behaviors and cause damage to the reputation of game companies. We examined in-game transactions to reveal RMT by constructing a social graph of virtual goods exchanges in an online game and identifying network communities of users. We analyzed approximately 6,000,000 transactions in a popular online game and inferred RMT transactions by comparing the RMT transactions crawled from an out-game market. Our findings are summarized as follows: (1) the size of the RMT market could be approximately estimated; (2) professional RMT providers typically form a specific network structure (either star-shape or chain) in the trading network, which can be used as a clue for tracing RMT transactions; and (3) the observed RMT market has evolved over time into a monopolized market with a small number of large-sized virtual goods providers.
In this paper, we provide valuable information to prove the claims made in previous studies. For example, Heeks @cite_3 explained that RMT providers pursued economies of size and scale in the RMT market. We confirmed that this phenomenon was observed through our analysis of the virtual goods trading networks in the real game dataset.
@cite_3
1754697193 48842013 2090459604 1537415400
This paper is to provide a theoretical investigation on real-money trading (RMT) observed frequently in online games. To complement former studies focused much on irregularity of transaction itself, economic incentives behind RMT are modeled and identified by reconsidering related economic studies. First, RMT is analyzed by economic incentives of online game players. Second, economic impacts of RMT are explored in the context of network externalities. Third, welfare implication with respect to game servicing firm and players is addressed in a dynamic context. Fourth, two issues of RMT, gold farming and micro-payment, are shortly addressed as mini-cases for the analysis. This paper has three purposes. First, it extends the range of economic ideas that have been applied to massively-multiplayer online games (MMOGs), drawing on scale economies, exchange rates, and information failure. It does this, as its second purpose, by deepening the analysis of one relatively-neglected aspect of virtual economies—gold farming (the production of MMOG virtual currencies, items, and services for financial gain) and trading—in order to understand in-game, out-game, and hybrid aspects of this activity. Third, the paper draws conclusions about two key real virtual issues on which earlier literature has disagreed. One is the extent to which standard real-world economic models are applicable to virtual economies. The paper argues a strong fit of standard models for analysis of gold farming and trading with little need for modification, but that MMOGs may be better understood through the lens of development economics rather than mainstream economics. The other issue discussed is the nature of the relation between the real and the virtual. On this, the paper concludes that gold farming is part of a dynamic that has eroded the real virtual dichotomy. At the least, gold farming and trading represents the intersection and blurring of the real and the virtual. At most, it reflects their indistinguishability. Finally, the paper ends by identifying alternative systemic models for understanding gold farming specifically, and MMOGs more generally. One of the main reasons of the recent success of peer to peer (P2P)file sharing systems such as BitTorrent is their built-in tit-for-tat mechanism. In this paper, we model the bandwidth allocation in a P2P system as an exchange economy and study a tit-for-tat dynamics, namely the proportional response dynamics, in this economy. In aproportional response dynamics each player distributes its good to its neighbors proportional to the utility it received from them in thelast period. We show that this dynamics not only converges but converges to a market equilibrium, a standard economic characterization of efficient exchanges in a competitive market. In addition, for some classes of utility functions we consider, it converges much faster than the classical tat process and any existingalgorithms for computing market equilibria. As a part of our proof we study the double normalization of a matrix, an operation that linearly scales the rows of a matrix sothat each row sums to a prescribed positive number, followed by a similar scaling of the columns. We show that the iterative double normalization process of any non-negative matrix always converges. This complements the previous studies in matrix scaling that has focused on the convergence condition of the process when the row and column normalizations are considered as separate steps. This paper reports statistical analyses performed on simulated data from a stochastic multi-agent model of speculative behaviour in a financial market. The price dynamics resulting from this artificial market process exhibits the same type of scaling laws as do empirical data from stock markets and foreign exchange markets: (i) one observes scaling in the probability distribution of relative price changes with a Pareto exponent around 2.6, (ii) volatility shows significant long-range correlation with a self-similarity parameter H around 0.85. This happens although we assume that news about the intrinsic or fundamental value of the asset follows a white noise process and, hence, incorporation of news about fundamental factors is insufficient to explain either of the characteristics (i) or (ii). As a consequence, in our model, the main stylised facts of financial data originate from the working of the market itself and one need not resort to scaling in unobservable extraneous signals as an explanation of the source of scaling in financial prices. The emergence of power laws can be explained by the existence of a critical state which is repeatedly approached in the course of the system's development.