Predictions in social sciences and adaptive blurry systems: application to the study of attitudes towards immigration
Abstract
The complementariety between quantitative and qualitative, macro- and micro approaches in Sociology is one of the more interesting lines of research in current sociology. New theoretical developments, joined to neural networks and fuzzy logic, as well as the new software, are allowing new perspectives. In this paper, from the point of view of Engineerings - Robotics and Sociology, a neurofuzzy algorithm is applied to analyze data from the Andalusian Social Survey 2003 in order to know more about factors with influence on the attitudes towards immigration. This neurofuzzy application opens new and complementary ways for the sociological knowledge (but it doesn’t substitute the existent ones) and it allows to discard some variables in the explanation of attitudes towards immigration. The methodological routine we have followed is easy to transfer to others spheres from the social research. And they are opening interesting ways for the research combining quantitative and qualitative data.Downloads
Published
2008-01-01
How to Cite
Gualda Caballero, E., & Sánchez Pérez, O. (2008). Predictions in social sciences and adaptive blurry systems: application to the study of attitudes towards immigration. Spanish Journal of Sociology, (5). Retrieved from https://recyt.fecyt.es/index.php/res/article/view/64984
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