2013/01/28 by Corrado Monti, Monti, Corrado, Alessandro Rozza +9
Physics and Astronomy · Social Sciences · #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Media Influence and Politics #Misinformation and Its Impacts #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1301.6630
openalex publication_date 2013/01/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In our work we analyse the political disaffection or "the subjective feeling of powerlessness, cynicism, and lack of confidence in the political process, politicians, and democratic institutions, but with no questioning of the political regime" by exploiting Twitter data through machine learning techniques. In order to validate the quality of the time-series generated by the Twitter data, we highlight the relations of these data with political disaffection as measured by means of public opinion surveys. Moreover, we show that important political news of Italian newspapers are often correlated with the highest peaks of the produced time-series.