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In this article, the autors wanted to expose that the Internet has become very important tool of political communication between citizens and political representatives in modern world and that its importance is increasing. In recent years the advent of new tools and social networks demonstrates true strenght of medium such as the Internet. The Internet, as a new medium, appeared quite recently, at the end of the 20th century. This medium creates new opportunities in political communication. Besides direct access to the public, it provides full force confrontation, but also provides a relatively convenient ground for review of public attitudes, research and development of certain ideas, and direct channel of communication with public and voters and also other influential interests groups. Internet increased mutual confrontation between voters and political representatives and created space for a higher degree of control of the political process by the public. In recent years, politicians have begun to take advantage of the Internet especially in the election campaign which proved to be very successful tool of communication with voters. The analysis was based on modern and available studies and surveys and on our own research. [ABSTRACT FROM AUTHOR]

The k-Nearest-Neighbours(kNN) is a simple and effective method for data classification. One of the major drawbacks of kNN is its low efficiency in its testing phase due to the lack of an explicit classification model. Recently, kNN model-based classifiers have been proposed to improve the conventional kNN. However, their building incurs high computational costs. In this paper, we tackle the model building problem by developing a cluster-based training algorithm to learn an optimized set of representatives that approximate the distributions of training data. The training algorithm adopts a fuzzy clustering method for unsupervised learning on the partial training set, and has a linear time complexity with respect to the size of the set. The experimental results conducted on real-world datasets demonstrate that the new method outperforms the previous kNN model-based classifier in the accuracy and possesses outstanding efficiency compared to kNN based classifiers. [ABSTRACT FROM PUBLISHER]

This study uses linear growth models to examine national changes in women?s representation in the European Parliament over five legislative periods from 1979-99. We examine two models: one measures broad processes of economic and cultural development, while the other assesses the institutional changes associated with political reform. Both models help explain the growth of female parliamentarians during the period, although the effects of improving the political opportunity structure are more consistent and a slightly better fit to the observed data. We also identify several variables with varying effects over time. We conclude that improvements in women?s representation are best viewed as the result of the processes of political democratization. [ABSTRACT FROM AUTHOR]