Fast Community Identification by Hierarchical Growth

A new method for community identification is proposed which is founded on the analysis of successive neighborhoods, reached through hierarchical growth from a starting vertex, and on the definition of communities as a subgraph whose number of inner connections is larger than outer connections. In order to determine the precision and speed of the method, it is compared with one of the most popular community identification approaches, namely Girvan and Newman's algorithm. Although the hierarchical growth method is not as precise as Girvan and Newman's method, it is potentially faster than most community finding algorithms.Comment: 6 pages, 5 figure

Assessing consumer literacy on financial complex products

Consumer financial education has become an important research topic, due to the growth of a wide range of investment products available in online banking. The individuals are exposed to highly complex financial products without understanding the risk and what product is suitable for them. This study investigates and measured the financial education of individuals in complex financial products. A quiz game was developed for a bank website to measure 1597 bank clients in complex products literacy. The survey also enabled a comparison between the basic and advanced skills of financial literacy knowledge. The results highlight a satisfactory overall financial literacy level. While basic knowledge level between individuals has a higher degree, there are serious concerns in advanced skill level. This study contributes to an understanding of adults’ knowledge about the prediction of the risk of investments in complex financial products, as well as providing value to ongoing financial literacy research.info:eu-repo/semantics/acceptedVersio

Gamification to teach and assess financial education: a case study of self-directed bank investors

Financial education has become a popular research topic, due the growth of marketing financial services, and the wide range and complexity of investment products available online. To assess the investment risk, and decide what product is suitable for individuals, it becomes essential to use tools to improve financial education. An educational game may be a possible solution since is a serious game designed to teach adults about a specific subject and to teach them a skill. Games-based learning software are interactive play that helps to solve problems, teaches, and gives the fundamental needs of learning by providing – enjoyment and motivation. This study investigates the financial education of self-directed investors in complex financial products, and portfolio management to answer our research question – how well adult self-directed investors understand financial education about complex financial products and portfolio management – and evaluates the financial education level of self-directed bank investors in complex financial products with high risk. An online quiz game with multiple-choice questions was developed, and deployed on a bank website to assess knowledge across investment product literacy - in addition to sociodemographic characteristics – involving the participation of 1,597 self-directed adult investors. The survey also enabled a comparison between the core and advanced skills of financial education knowledge. To measure and assess the financial education, we calculate the individual score by the amount of correct answers from the three multiple answer quiz questions. The results highlight that participants have a satisfactory overall financial literacy level. While core competencies, knowledge among private investors have a higher degree of general financial education, there are particular areas in which they scored low in advanced skills (i.e., complex financial product questions). This result provides valuable insights, information for further investigation of distance education research through games, which can only continue to grow because of the increasing complexity and importance of financial education in modern societies. This study contributes to an understanding of adults’ knowledge regarding investments in complex financial products, as well as providing a valuable contribution to ongoing financial education research.info:eu-repo/semantics/acceptedVersio

How to develop financial applications with game features in e-banking?

As for Gamification, it is about business software with game characteristics, understanding the software development process will improve the practices, and will more than likely, improve the business itself (make it more efficient, effective, and less costly and mainly collect a positive influence from the customers). This study aims to develop a framework that provides the mechanisms to ensure that the software will have game characteristic and that clients will recognize it as Gamification. Our results show that the five-step framework proposal applied to the Gamification project management on this study, the Spiral development model, and the group discussion results into a positive effect on customers and e-business. The spiral development methodology used for the development of this application showed to be the appropriated for this type of project. The tests with discussion-groups proved to be a key "tool" to identify and adapt the game characteristics that has led to the improvement of customer perception of socialness, usefulness ease of use, enjoyment and ease of use that probed to have a strong positive impact on the intention to use the game.info:eu-repo/semantics/acceptedVersio

Surviving opinions in Sznajd models on complex networks

The Sznajd model has been largely applied to simulate many sociophysical phenomena. In this paper we applied the Sznajd model with more than two opinions on three different network topologies and observed the evolution of surviving opinions after many interactions among the nodes. As result, we obtained a scaling law which depends of the network size and the number of possible opinions. We also observed that this scaling law is not the same for all network topologies, being quite similar between scale-free networks and Sznajd networks but different for random networks.Comment: 9 pages, 3 figure

Tuned liquid dampers simulation for earthquake response control of buildings

This paper is focused on the study of an earthquake protection system, the Tuned Liquid Damper (TLD), which can, if adequately designed, reduce earthquake demands on buildings. This positive effect is accomplished taking into account the oscillation of the free surface of a fluid inside a tank (sloshing). The behaviour of an isolated Tuned Liquid Damper, subjected to a sinusoidal excitation at its base, with different displacement amplitudes, was studied by finite element analysis. The efficiency of the TLD in improving the seismic response of an existing building, representative of modern architecture buildings in southern European countries was also evaluated based on linear dynamic analyses

A systematic comparison of supervised classifiers

Pattern recognition techniques have been employed in a myriad of industrial, medical, commercial and academic applications. To tackle such a diversity of data, many techniques have been devised. However, despite the long tradition of pattern recognition research, there is no technique that yields the best classification in all scenarios. Therefore, the consideration of as many as possible techniques presents itself as an fundamental practice in applications aiming at high accuracy. Typical works comparing methods either emphasize the performance of a given algorithm in validation tests or systematically compare various algorithms, assuming that the practical use of these methods is done by experts. In many occasions, however, researchers have to deal with their practical classification tasks without an in-depth knowledge about the underlying mechanisms behind parameters. Actually, the adequate choice of classifiers and parameters alike in such practical circumstances constitutes a long-standing problem and is the subject of the current paper. We carried out a study on the performance of nine well-known classifiers implemented by the Weka framework and compared the dependence of the accuracy with their configuration parameter configurations. The analysis of performance with default parameters revealed that the k-nearest neighbors method exceeds by a large margin the other methods when high dimensional datasets are considered. When other configuration of parameters were allowed, we found that it is possible to improve the quality of SVM in more than 20% even if parameters are set randomly. Taken together, the investigation conducted in this paper suggests that, apart from the SVM implementation, Weka's default configuration of parameters provides an performance close the one achieved with the optimal configuration