By Shu-Heng Chen, Takao Terano, Ryuichi Yamamoto, Chung-Ching Tai

This quantity is a post-conference ebook of the 4th global Congress on Social Simulation (WCSS), with contents chosen from one of the eighty papers initially awarded on the convention. WCSS is a biennial occasion, together geared up via 3 clinical groups in computational social technology, particularly, the Pacific-Asian organization for Agent-Based technique in Social structures Sciences (PAAA), the ecu Social Simulation organization (ESSA), and the Computational Social technology Society of the Americas (CSSSA). it really is, consequently, at present the main favorite convention within the sector of agent-based social simulation. The papers chosen for this quantity provide a holistic view of the present improvement of social simulation, indicating the instructions for destiny learn and developing an incredible archival record and milestone within the historical past of computational social technological know-how. particularly, the papers incorporated the following hide great growth in man made monetary markets, macroeconomic forecasting, offer chain administration, financial institution networks, social networks, city making plans, social norms and workforce formation, cross-cultural experiences, political celebration pageant, balloting habit, computational demography, computational anthropology, evolution of languages, public future health and epidemics, AIDS, defense and terrorism, methodological and epistemological concerns, empirical-based agent-based modeling, modeling of experimental social technological know-how, gaming simulation, cognitive brokers, and participatory simulation. additionally, pioneering reports in a few new examine parts, comparable to the theoretical foundations of social simulation and specific social technological know-how, are also incorporated within the volume.

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They found that the content of messages might possibly be used to explain stock returns, though the number of messages could not. However, they pointed out that the BMB cannot explain all residual returns. They classified the content of messages by using only one dimension such as bullishbearish. Previous studies found that text data can be classified in several dimensions. Similarly, messages on BBSs might be classified in dimensions other than bullishbearish. The purpose of our research is thus to develop a new factor based on BBSs, instead of the BMB, to explain stock returns.

7) kD1 Although it seems unrealistic to assume that readers choose blogs based on the advertising of their favorite products, product congruence could be a good proxy for similarity in taste for consumption. In addition, if affiliates are able to find an ad mix that is most congruent to the target readers’ product preferences, the resulting links will maximize this congruence. In that sense, this congruence could measure the “optimality” of the affiliates’ actions. The links maximizing topic congruence and product congruence are, respectively, extremes of a continuum of the possible links between the agents.

If a PCS correlated with a stock return, the principal component analysis might be able to explain the return. Moreover, if the PCS did not correlate with bullishness, it might be a candidate for a new factor, because the BMB is based on bullishness. 1 Definition of portfolio 9 Portfolio Definition PF1 PF2 PF3 PF4 PF5 PFX First quintile of the PCSs Second quintile of the PCSs Third quintile of the PCSs Fourth quintile of the PCSs Fifth quintile of the PCSs None of messages According to Maruyama et al.

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