110,794 research outputs found

    User identification based on game-play activity patterns

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    Using Gameplay Patterns to Gamify Learning Experiences

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    Gamification refers to the use of gaming elements to enhance user experience and engagement in non-gaming systems. In this paper we report the design and implementation of two higher education courses in which ludic elements were used to enhance the quality of the learning experience. A game can be regarded as a system of organised gameplay activities, and a course can be regarded as a system of organised learning activities. Leveraging this analogy, analysing games can provide valuable insights to organise learning activities within a learning experience. We examined a sample of successful commercial games to identify patterns of organisation of gameplay activities that could be applied to a course design. Five patterns were identified: quest structure, strategic open-endedness, non-linear progression, orientation, and challenge-based reward. These patterns were then used to define the instructional design of the courses. As a result, courses were organised as systems of quests that could be tackled through different strategies and in a non-linear way. Students received frequent feedback and were rewarded according to the challenges chosen, based on mechanics common in quest-based games. The courses involved two lecturers and 70 students. Learning journals were used throughout the term to collect data regarding student perceptions on the clarity and usefulness of the gamified approach, level of motivation and engagement in the courses, and relevance of the activities proposed. Results show that students felt challenged by the activities proposed and motivated to complete them, despite considering most activities as difficult. Students adopted different cognitive and behavioural strategies to cope with the courses’ demands. They had to define their own team project, defining the objectives, managing their times and coordinating task completion. The regular and frequent provision of feedback was highly appreciated. A sense of mastery was promoted and final achievement was positively impacted by the gamified strategy

    An empirical biometric-based study for user identification from different roles in the online game League of Legends

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    © 2017 CEUR-WS. All rights reserved. The popularity of computer games has grown exponentially in the last few years. In some games, players can choose to play with different characters from a pre-defined list, exercising distinct roles in each match. Although such games were created to promote competition and promote self-improvement, there are several recurrent issues. One that has received the least amount of attention is the problem of "account sharing" so far is when a player pays more experienced players to progressing in the game. The companies running those games tend to punish this behaviour, but this specific case is hard to identify. The aim of this study is to use a database of mouse and keystroke dynamics biometric data of League of Legends players as a case study to understand the specific characteristics a player will keep (or not) when playing different roles and distinct characters

    Modeling Paying Behavior in Game Social Networks

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    Online gaming is one of the largest industries on the Internet, generating tens of billions of dollars in revenues annually. One core problem in online game is to find and convert free users into paying customers, which is of great importance for the sustainable development of almost all online games. Although much research has been conducted, there are still several challenges that remain largely unsolved: What are the fundamental factors that trigger the users to pay? How does users? paying behavior influence each other in the game social network? How to design a prediction model to recognize those potential users who are likely to pay? In this paper, employing two large online games as the basis, we study how a user becomes a new paying user in the games. In particular, we examine how users' paying behavior influences each other in the game social network. We study this problem from various sociological perspectives including strong/weak ties, social structural diversity and social influence. Based on the discovered patterns, we propose a learning framework to predict potential new payers. The framework can learn a model using features associated with users and then use the social relationships between users to refine the learned model. We test the proposed framework using nearly 50 billion user activities from two real games. Our experiments show that the proposed framework significantly improves the prediction accuracy by up to 3-11% compared to several alternative methods. The study also unveils several intriguing social phenomena from the data. For example, influence indeed exists among users for the paying behavior. The likelihood of a user becoming a new paying user is 5 times higher than chance when he has 5 paying neighbors of strong tie. We have deployed the proposed algorithm into the game, and the Lift_Ratio has been improved up to 196% compared to the prior strategy

    Project:Filter - using applied games to engage secondary schoolchildren with public policy

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    Applied games present a twenty-first-century method of consuming information for a specific purpose beyond pure entertainment. Objectives such as awareness and engagement are often used as intended outcomes of applied games in alignment with strategic, organizational, or commercial purposes. Applied games were highlighted as an engagement-based outcome to explore noPILLS, a pan-European policy research project which presented policy pointers and suggested methods of interventions for reducing micropollution within the wastewater treatment process. This paper provides an assessment of a video game which was developed for the purpose of public engagement with policy-based research. The video game, Project:Filter, was developed as a means of communicating noPILLS to secondary school children in Scotland as part of a classroom-based activity. Knowledge development and engagement were identified using Interpretative Phenomenological Analysis to evidence topical awareness, depth of understanding, and suggested methods of intervention. Analysis of observations also provided insights into challenges surrounding logistics, pedagogy, social interactions, learning, and gender as contributing factors to the schoolchildren’s experiences of Project:Filter. The intention of this paper is two-fold: firstly, to provide an example of developing video games from policy-based research; and secondly, to suggest methods of phenomenological assessment for identifying play-based engagement

    Crime Scene Re-investigation: A Postmortem Analysis of Game Account Stealers' Behaviors

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    As item trading becomes more popular, users can change their game items or money into real money more easily. At the same time, hackers turn their eyes on stealing other users game items or money because it is much easier to earn money than traditional gold-farming by running game bots. Game companies provide various security measures to block account- theft attempts, but many security measures on the user-side are disregarded by users because of lack of usability. In this study, we propose a server-side account theft detection system base on action sequence analysis to protect game users from malicious hackers. We tested this system in the real Massively Multiplayer Online Role Playing Game (MMORPG). By analyzing users full game play log, our system can find the particular action sequences of hackers with high accuracy. Also, we can trace where the victim accounts stolen money goes.Comment: 7 pages, 8 figures, In Proceedings of the 15th Annual Workshop on Network and Systems Support for Games (NetGames 2017
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