Narrow Results

We study a large social network consisting of 3 × 10⁴ individuals, who interact in a large virtual world of Massive Multiplayer Online Role Playing Games (MMORPGs). On the basis of the players' list of friends and the playing time received from the on-line game server, we investigate the structure of the network and human dynamics. We try to show that the structure of this friendship network is very similar to the structure of different social networks. In order to investigate the relation between networks of acquaintances in virtual and real worlds, we carried out a survey among the players. We found very interesting scaling laws concerning human dynamics. Our research has shown how long people are interested in a single task, and how much time they devote to it. It is surprising that exponent values in both cases are close to minus one.

There is sufficient evidence to support that the inter-event time distribution of human behaviors is heavy tailed. This fact plays an important role in human dynamics at collective levels. Recently, researchers found that the heavy-tailed inter-activity patterns of human behaviors slow down the spreading significantly. In this paper, we investigate the influence of people's interest time length on information spreading. Considering that information has its own time period of being interested in, we find that for small interest time period, heavy-tailed human behaviors can enhance the information spreading. While for large interest time period, the heavy-tailed human behaviors will suppress the spreading. These results can help us understanding the rule of information spreading, controlling and limiting the outbreak of rumors.

The interpretation and characterization of universal scaling laws in human mobility and activity are subjects of active research. For the better understanding, instead of the statistical approach we have examined the temporal patterns of human daily motion using location data. The trajectories were measured continuously and with even sampling (1 measurement per minute), using GPS and Wi-Fi/mobile Internet signals of the participant’s smartphone, we have analyzed the few-week-long signals of displacements between two subsequent samplings in frequency domain. Our results had shown that 1/$f$ type noise is observable over the frequency of the daily rhythm of motion and its harmonics. We point out several technical questions about the measurement and data processing required for further detailed analysis. Furthermore, our new observation could help in the investigation of the underlying dynamics of human motion and opens several theoretical questions about the relationship between the spatial and temporal universality.

Based on the theory of multi-rigid body systems, a dynamic analysis model is established for human bones. For each joint in the human skeletal model, corresponding to the rotation joint, universal joint, and ball joint in the rigid body system, they are characterized to have single, double, and three degrees of freedom, respectively. Furthermore, the rotational changes between each joint are represented by the directional cosine matrix. The relationship is given between displacement and the bone center of mass. During the experiment, figure skaters were selected as the test subjects and waltz jumps were used as the test movements. Based on the human skeletal dynamics model, the angle change curves of the left hip joint, knee joint, and ankle joint were obtained, and a comparison with the standard action was formed. The conclusion shows that the proposed human body dynamics analysis method can assist in the scientific training of figure skating.