Empirical studies on the network of social groups: the case of Tencent QQ

Participation in social groups are important but the collective behaviors of human as a group are difficult to analyze due to the difficulties to quantify ordinary social relation, group membership, and to collect a comprehensive dataset. Such difficulties can be circumvented by analyzing online social networks. In this paper, we analyze a comprehensive dataset obtained from Tencent QQ, an instant messenger with the highest market share in China. Specifically, we analyze three derivative networks involving groups and their members -- the hypergraph of groups, the network of groups and the user network -- to reveal social interactions at microscopic and mesoscopic level. Our results uncover interesting behaviors on the growth of user groups, the interactions between groups, and their relationship with member age and gender. These findings lead to insights which are difficult to obtain in ordinary social networks.Comment: 18 pages, 9 figure

Investors’ Attention Allocation to Stock Analysis: The Role of Rating Deviation

Stock analysis is important for investors. However, little is known about how investors allocate their attention to different analyses. In the last two decades, online investment communities (OICs) have proliferated. In this study, we use investors’ online activities (i.e., comment and like) and amateur stock analysis in Seeking Alpha to explore how investors allocate their attention among different analyses by examining the effects of stock rating deviation on their attention. We measure the stock rating deviation of one analysis by comparing its stock rating with the previous rating for the same stock. The results show that the analyses with stock ratings that are more deviated from the existing ratings tend to receive more comments and likes from investors, indicating that rating deviation from the consensus positively impacts investor attention to stock analysis. In addition, the deviation’s negativity and the stock volatility strengthen the impact of rating deviation on investor attention. However, analysts’ busyness status negatively moderates this impact

Preparation and Characterization of Waterborne Polyurethaneurea Composed of Dimer Fatty Acid Polyester Polyol

A series of polyurethaneurea (PUU) aqueous dispersions, which were stable at ambient temperature for more than 1 year, were prepared with C36-dimer-fatty-acid-based polyester polyol, isophorone diisocyanate, dimethylol propionic acid, and ethylenediamine. The particle size of all these PUU (DPU) aqueous dispersions (<100 nm) was less than that of comparable specimens, that is, poly-(neopentyl glycol adipate) polyester-polyol-based PUU (APU) aqueous dispersions, and the polydispersity index was very narrow (≤1.13). The films prepared with the DPU aqueous dispersions exhibited excellent waterproof performance, such as low amount of water absorption (1.3 wt%), and good mechanical properties (hardness and tensile strength), resulting from the strong hydrogen bonding in urea carbonyl groups and the perfect ordered structure of hard segments compared with those prepared with the APU aqueous dispersions. The surface hydrophobicity of the films prepared with modified DPU aqueous dispersions, which were modified with a fluorinated polyacrylate emulsion, was excellent, as the water contact angle on the surface of such films rose up to 100. The mechanical properties of such modified DPU films were further enhanced

Origin of the Scaling Law in Human Mobility: Hierarchical Organization of Traffic Systems

Uncovering the mechanism leading to the scaling law in human trajectories is of fundamental importance in understanding many spatiotemporal phenomena. We propose a hierarchical geographical model to mimic the real traffic system, upon which a random walker will generate a power-law travel displacement distribution with exponent -2. When considering the inhomogeneities of cities' locations and attractions, this model reproduces a power-law displacement distribution with an exponential cutoff, as well as a scaling behavior in the probability density of having traveled a certain distance at a certain time. Our results agree very well with the empirical observations reported in [D. Brockmann et al., Nature 439, 462 (2006)].Comment: 6 figures, 4 page