Abstract: Gold farming refers to the illicit practice of gathering and selling virtual goods in online games for real money. Although around one million gold farmers engage in gold farming related activities, to date a systematic study of identifying gold farmers has not been done. Here data is used from the Massively Multiplayer Online Role Playing Game (MMOG) EverQuest II to identify gold farmers. This is posed as a binary classification problem and a set of features is identified for classification purposes. Given the cost associated with investigating gold farmers, criteria are also given for evaluating gold farming detection techniques, and suggestions provided for future testing and evaluation techniques.

Abstract: A massively multiplayer online game (MMOG) monetization analysis computer system may include an electronic data processing system configured to electronically analyze data, including player behavioral logs, in accordance with one or more algorithms. Based on the analysis, the electronic data processing system may predict player changes that are relevant to monetization of the MMOG and generate a report relating to these predicted changes. The analysis may identify players whom are predicted to terminate their subscriptions to the MMOG, an amount of time each of several players is likely to spend playing the MMOG, and/or a number of transactions each of a several players is likely to engage in while playing the MMOG.