Ji-Lung Hsieh

Player Guild Dynamics and Evolution in Massively Multiplayer Online Games

In the latest versions of massively multiplayer online games (MMOGs), developers have purposefully made guilds part of game environments. Guilds represent a powerful method for giving players a sense of online community, but there is little quantitative data on guild dynamics. To address this topic, we took advantage of a feature found in one of todays most popular MMOGs (World of Warcraft) to collect in-game data: user interfaces that players can modify and refine. In addition to collecting data on in-game player activities, we used this feature to observe and investigate how players join and leave guilds. Data were analyzed for the purpose of identifying factors that propel game-world guild dynamics and evolution. After collecting data for 641,805 avatars on 62 Taiwanese World of Warcraft game servers between February 10 and April 10, 2006, we created five guild type categories (small, large, elite, newbie, and unstable) that have different meanings in terms of in-game group dynamics. By viewing players as the most important resource affecting guild life cycles, it is possible to analyze game worlds as ecosystems consisting of evolving guilds and to study how guild life cycles reflect game world characteristics.

Building a player strategy model by analyzing replays of real-time strategy games

Developing computer-controlled groups to engage in combat, control the use of limited resources, and create units and buildings in real-time strategy (RTS) games is a novel application in game AI. However, tightly controlled online commercial game pose challenges to researchers interested in observing player activities, constructing player strategy models, and developing practical AI technology in them. Instead of setting up new programming environments or building a large amount of agentpsilas decision rules by playerpsilas experience for conducting real-time AI research, the authors use replays of the commercial RTS game StarCraft to evaluate human player behaviors and to construct an intelligent system to learn human-like decisions and behaviors. A case-based reasoning approach was applied for the purpose of training our system to learn and predict player strategies. Our analysis indicates that the proposed system is capable of learning and predicting individual player strategies, and that players provide evidence of their personal characteristics through their building construction order.

A Novel Small-World Model: Using Social Mirror Identities for Epidemic Simulations

The authors propose a small-world network model that combines cellular automata with the social mirror identities of daily-contact networks for purposes of performing epidemiological simulations. The social mirror identity concept was established to integrate human long-distance movement and daily visits to fixed locations. After showing that the model is capable of displaying such small-world effects as low degree of separation and relatively high degree of clustering on a societal level, the authors offer proof of its ability to display R 0 properties—considered central to all epidemiological studies. To test their model, they simulated the 2003 severe acute respiratory syndrome (SARS) outbreak.

Teaching through Simulation: Epidemic Dynamics and Public Health Policies

A growing number of epidemiologists are now working to refine computer simulation methods for diseases as a strategy for helping public policy decision-makers assess the potential efficacies of tactics in response to newly emerging epidemics. These efforts spiked after the SARS outbreak of 2002– 2003. Here we describe our attempt to help novice researchers understand epidemic dynamics with the help of the cellular automata with social mirror identity model (CASMIM), a small-world epidemiological simulation system created by Huang et al. in 2004. Using the SARS scenario as a teaching example, we designed three sets of instructional experiments to test our assumptions regarding (i) simulating epidemic transmission dynamics and associated public health policies, (ii) assisting with understanding the properties and efficacies of various public health policies, (iii) constructing an effective, low-cost (in social and financial terms) and executable suite of epidemic prevention strategies, and (iv) reducing the difficulties and costs associated with learning epidemiological concepts. With the aid of the proposed simulation tool, novice researchers can create various scenarios for discovering epidemic dynamics and for exploring applicable combinations of prevention or suppression strategies. Results from an evaluative test indicate a significant improvement in the ability of a group of college students with little experience in epidemiology to understand epidemiological concepts.

Influences of Resource Limitations and Transmission Costs on Epidemic Simulations and Critical Thresholds in Scale-Free Networks

Critical thresholds represent one of the most important diffusion indicators of epidemic outbreaks. However, we believe that recent studies have overemphasized ways that the power-law connectivity distribution features of social networks affect epidemic dynamics and critical thresholds. As a result, two important factors have been overlooked: resource limitations and transmission costs associated with social interactions and daily contact. Here we present our results from the simultaneous application of mean-field theory and an agent-based network simulation approach for analyzing the effects of resources and costs on epidemic dynamics and critical thresholds. Our main findings are: (a) a significant critical threshold does exist when resources and costs are taken into consideration, and it has a lower bound whenever contagion events occur in scale-free networks; (b) when transmission costs increase or individual resources decrease, critical contagion thresholds in scale-free networks grow linearly and steady density curves shrink linearly; (c) regardless of whether the resources of individuals obey delta, uniform, or normal distributions, they have the same critical thresholds and epidemic dynamics as long as the average value of usable resources remains the same across different scale-free networks; and (d) the spread of epidemics in scale-free networks remains controllable as long as resources are properly restricted and intervention strategy investments are significantly increased.

Learning to build network-oriented epidemic simulation models in epidemiology education

Epidemic simulations and intervention strategy assessments are attracting interest in light of recent and potential outbreaks of infectious diseases such as SARS and avian flu. Universities are using computational modelling and simulation tools to teach epidemiology concepts to students, but integrating domain-specific knowledge and building network-based simulation models are difficult tasks in terms of teacher preparation and learner evaluation. To illustrate challenges to creating network-oriented models in epidemiology education, we introduce an architecture based on demographic and geographic data for building network-oriented epidemic simulation models, and describe our experiences simulating the transmission dynamics of three infectious diseases in Taiwan.

Taiwanese Facebook Users’ Motivation and the Access of Information Technology

With the increasing diversity in networked information communication technology (ICTs), the question arises whether users’ social, entertainment and information needs are being met. Existing research on Internet information services and traditional portal or blog sites has not been extended to a more recent study of functional community websites such as Facebook. Therefore, this study was designed to administer a questionnaire survey in order to explore the motivation of Taiwan Facebook users of ICT’s by analyzing their Facebook use. The study concluded that: (1) Facebook users were attracted to Facebook mainly by social motivations, though some were attracted by the Facebook game simulation of “Farmville”, highly publicized in the media. A study of background variables further found that female users who had low education level and low age were more likely motivated by the gaming platform; male users who had low education level and a higher age were likely attracted by both a high degree of social interaction and high use of game-playing; (2) Facebook users were online more often, but for most there was no significant increase in the total number of hours online; (3) Facebook users who were motivated by both game play and social interaction do actually increase their online time using Facebook. The study indicated that Facebook facilitates increased use of information technology, and further recognizes that the gender of users accounts for significant differences in motivation. The findings of this study will lead to a better understanding of the motivation of Taiwan ICT users, specifically Taiwan Facebook users.

Using Evolving Agents to Critique Subjective Data: Recommending Music

The authors describe a recommender model that uses intermediate agents to evaluate a large body of subjective data according to a set of rules and make recommendations to users. After scoring recommended items, agents adapt their own selection rules via interactive evolutionary computing to fit user tastes, even when user preferences undergo a rapid change. The model can be applied to such tasks as critiquing large numbers of music, image, or written compositions. In this paper we use musical selections to illustrate how agents make recommendations and report the results of several experiments designed to test the models ability to adapt to rapidly changing conditions yet still make appropriate decisions and recommendations.

Author publication preferences and journal competition

The processes that authors use to publish their papers in journals can be analyzed in terms of field‐specific practices. How they select targeted publications can influence competitive relationships among journals. In this paper, the author quantifies the publishing choices of a set of scholars to confirm this ecological perspective. The results indicate a strong focus on a small number of journals. A measure of author publishing choices was used to define four ecological characteristics: coverage, coreness, exclusivity, and journal overlap. Several types of journals indexed in the Information Science and Library Science section of the Journal Citation Reports are compared in terms of their ecological characteristics. The data show that some journals cover large numbers of authors, but compete with other journals in subcommunities. Some journals with author profiles similar to those of high‐ranking journals lost potential submissions. Others with low coverage, high coreness, and high exclusivity were found to have groups of “fans” who used them for all of their submissions, but still exhibited a strong need to sustain their exclusivity. It is hoped that the method and results presented in this paper will provide useful information for editorial boards interested in managing their submissions according to author profiles.

Bridge and Brick Network Motifs

Researchers are increasingly acknowledging the important role of complex networks in numerous scientific contexts. In this paper we define two kinds of motifs - bridge and brick - for exploring and predicting network behaviors and functions and for identifying differences among network structures. Based on an analysis of these motifs in genetic, social, ecological, and engineering networks, we found significant differences in motif functionality and topology. After initially observing similarities between social networks and their genetic, ecological, and engineering counterparts, we eventually noted greater amounts of brick motif in social networks and greater amounts of bridge motif in the other three types. Our conclusion is that bridge and brick motif content analyses can assist researchers in understanding the small-world and clustering properties of network structures and in investigating network functions and behaviors