Resumen:
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[EN] In this work, we seek to highlight and describe the main differences between
traditional public opinion polls (made by using methods and techniques
traditionally undertaken in the social sciences), and those ...[+]
[EN] In this work, we seek to highlight and describe the main differences between
traditional public opinion polls (made by using methods and techniques
traditionally undertaken in the social sciences), and those accomplished
through methodological processes made possible by the adoption of big data.
We ensure a special focus on the consequences brought about by the use of
nonparametric analysis over parametric analysis to show how big data is
impacting not only the methodological aspects but the epistemological basis
of public opinion studies in general. Researchers see an epistemological
struggle between methodology and theory in public opinion studies. This
struggle is composed of two approaches: a quantitative one and a qualitative
one. On the one hand, we have quantitative polls methods which lead to an
excessively contextual representation of public opinion. On the other hand,
we have general theories that do grasp public opinion in most of its
complexity but fall short in providing sophisticated empirical tools for
contextual analysis of public opinion specific issues. The methods undertook
by pollsters, as many others used in social sciences rely upon classical
scientific structures, where researchers conduct their studies through
hierarchical theories and survey techniques to access and understand their
subject. In these cases, the researchers must pose the research problem a
prioristically, to parametrize and create the questionnaires before the
collecting of the data to be analyzed after. By using big data models, the need
for posing a research problem and parametrize the proceedings of the study
a prioristically no longer exists, thus contributing to a characterization of
public opinion that is qualitative and way more complex, rather than the
traditional one. Although not yet strictly statistically representative, public
opinion studies made by using datasets collected from social media provide
us with a view of public opinion that shows, among other things, the main
actors (persons, groups, and organizations), their powers of influence over
the others and their interests in public opinion formation movement.
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