Application of information and complexity theories to public opinion polls. The case of Greece (2004-2007)

TL;DR

This paper introduces a methodology based on information and complexity theories to analyze public opinion polls, providing quantitative insights into political approval and party support in Greece and the US.

Contribution

It extends existing models by incorporating complexity and Fisher information to quantify the organization of public opinion data.

Findings

High approval of Greek Prime Minister Karamanlis explained through information theory.

The same model applies to US President Clinton's popularity, showing its broader applicability.

Quantitative measures of opinion data organization are introduced.

Abstract

A general methodology to study public opinion inspired from information and complexity theories is outlined. It is based on probabilistic data extracted from opinion polls. It gives a quantitative information-theoretic explanation of high job approval of Greek Prime Minister Mr. Constantinos Karamanlis (2004-2007), while the same time series of polls conducted by the company Metron Analysis showed that his party New Democracy (abbr. ND) was slightly higher than the opposition party of PASOK -party leader Mr. George Papandreou. It is seen that the same mathematical model applies to the case of the popularity of President Clinton between January 1998 and February 1999, according to a previous study, although the present work extends the investigation to concepts as complexity and Fisher information, quantifying the organization of public opinion data.