Juyong Park

Topology and evolution of the network of western classical music composers

The expanding availability of high-quality, large-scale data from the realm of culture and the arts promises novel opportunities for understanding and harnessing the dynamics of the creation, collaboration, and dissemination processes - fundamentally network phenomena - of artistic works and styles. To this end, in this paper we explore the complex network of western classical composers constructed from a comprehensive CD (Compact Disc) recordings data that represent the centuries-old musical tradition using modern data analysis and modeling techniques. We start with the fundamental properties of the network such as the degree distribution and various centralities, and find how they correlate with composer attributes such as artistic styles and active periods, indicating their significance in the formation and evolution of the network. We also investigate the growth dynamics of the network, identifying superlinear preferential attachment as a major growth mechanism that implies a future of the musical landscape where an increasing concentration of recordings onto highly-recorded composers coexists with the diversity represented by the growth in the sheer number of recorded composers. Our work shows how the network framework married with data can be utilized to advance our understanding of the underlying principles of complexities in cultural systems.

Multi-relational social networks in a large-scale MMORPG

We analyze multi-relational social interaction networks in a large-scale commercial Massively Multiplayer Online Role-Playing Game(MMORPG). Our work is based on data from AION, currently the worlds second most-played MMORPG with 3.4 million subscribers as of mid 2010, created and serviced by NCSoft, Inc. We construct and characterize six distinct interactivity networks (Friend, Private Messaging, Party invitation, Trade, Mail, and Shop), each representing diverse player interaction types.

Altruism in games: Helping others help themselves

Altruistic behavior is often considered the building block of a civic society. As more people interact with others in online environments, altruistic behaviors therein have become an interesting issue for analysis. In this paper, we investigate it in MMORPGs (Massively Multiplayer Online Role-Playing Games) that provide the most realistic, lifelike experiences. Specifically we look at the altruistic behaviors in Aion, an MMORPG serviced by NC Soft, Inc., of Korea. We analyze two types of behaviors, namely donation of cyber assets and guided co-play with lowerlevel users. We find that benefiting from altruistic behaviors can initiate pay-it-forward phenomena, and increases a players customer loyalty and satisfaction from the game.

Bayesian Inference of Natural Rankings in Incomplete Competition Networks

Competition between a complex systems constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest – essential in determining reward and penalty – is frequently an ambiguous task due to the incomplete (partially filled) nature of competition networks. Here we introduce the “Natural Ranking,” an unambiguous ranking method applicable to a round robin tournament, and formulate an analytical model based on the Bayesian formula for inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in resolving important issues of ranking by applying it to real-world competition networks.

The Multi-Scale Network Landscape of Collaboration.

Propelled by the increasing availability of large-scale high-quality data, advanced data modeling and analysis techniques are enabling many novel and significant scientific understanding of a wide range of complex social, natural, and technological systems. These developments also provide opportunities for studying cultural systems and phenomena—which can be said to refer to all products of human creativity and way of life. An important characteristic of a cultural product is that it does not exist in isolation from others, but forms an intricate web of connections on many levels. In the creation and dissemination of cultural products and artworks in particular, collaboration and communication of ideas play an essential role, which can be captured in the heterogeneous network of the creators and practitioners of art. In this paper we propose novel methods to analyze and uncover meaningful patterns from such a network using the network of western classical musicians constructed from a large-scale comprehensive Compact Disc recordings data. We characterize the complex patterns in the network landscape of collaboration between musicians across multiple scales ranging from the macroscopic to the mesoscopic and microscopic that represent the diversity of cultural styles and the individuality of the artists.

Network Landscape of Western Classical Music

Network science has shown itself to be useful in understanding a complex system by allowing us to unearth novel and intriguing patterns among its components. It is playing a particularly integral role in understanding social systems where collaboration between people is essential. Music is one such domain, as evidenced by how its centuries-old history is filled with intriguing episodes of collaborations between its central personalities and the influences they exerted on one other. In this article, the authors present their findings in the network understanding of the landscape of collaborations in western classical music.

Ranking Competitors Using Degree-Neutralized Random Walks

Competition is ubiquitous in many complex biological, social, and technological systems, playing an integral role in the evolutionary dynamics of the systems. It is often useful to determine the dominance hierarchy or the rankings of the components of the system that compete for survival and success based on the outcomes of the competitions between them. Here we propose a ranking method based on the random walk on the network representing the competitors as nodes and competitions as directed edges with asymmetric weights. We use the edge weights and node degrees to define the gradient on each edge that guides the random walker towards the weaker (or the stronger) node, which enables us to interpret the steady-state occupancy as the measure of the nodes weakness (or strength) that is free of unwarranted degree-induced bias. We apply our method to two real-world competition networks and explore the issues of ranking stabilization and prediction accuracy, finding that our method outperforms other methods including the baseline win–loss differential method in sparse networks.

Moneymakers and bartering in online games

We study the interpersonal trade network from a Massively Multiplayer Online Role-Playing Game (MMORPG), where players actively engage in the exchange and sales of goods and items in a hyperrealistic virtual environment. In this paper we introduce the concept of Standard Price (SP) of items computed from the trade network, which allows us to investigate the relation between the profitability of a trade and the structure of the social networks of the users. We find that the social network is correlated with the outcome of interpersonal trades. For instance, we observe that the margin of profit in a trade correlates with the social distance between trading partners, suggesting that social affinity implies shared information on the value of an item.

The Network of Western Classical Musicians

The expanding availability of large-scale data is leading to increased opportunities for applying advanced data analysis and modeling methodology to a wide range of problems and systems, allowing us to deepen our understandings and make novel discoveries. In this paper we use the tools of network science to the network of composers and performers from the western classical music tradition constructed from an extensive data archive of CD recordings. We measure the fundamental characteristics of the network such as the small-world property and the power-law degree distribution. We also investigate the community structures of the musicians, revealing how individual attributes such as musical style, positions, and nationalities factor into the large-scale association patterns of the network. We believe that our work showcases the potential benefits of network science in the study of arts and humanities.

The Network of Western Classical Music Composers

Network science focuses on the connections between the elements of a complex system in order to uncover the nature and the underlying patterns of interaction relationships inside the system. In this paper we apply network theory to understand associations between the composers of western classical music constructed from a comprehensive data of CD recordings. We study the properties of the network of composer-composer ties including the degree distribution, the component structure, clustering, and several types of centralities of the composers. We also investigate the nature of prominent modules found in the network, and show how the tastes of consumers of western classical music manifest themselves in the network.We believe that our work shows how network science can be a useful tool for studying arts and humanities.