This contribution aims at investigating the changes in visual communication by Italian political leaders on Instagram during the outbreak of the Covid-19 pandemic. Using a dataset including all the posts published by the main Italian political leaders from September 20th, 2019 to September 20th, 2020 (n = 6,865) and using face and emotional recognition algorithms, we analyze the differences in the visual content proposed by populist and mainstream political actors. Results indicate that populist right leaders (Salvini and Meloni) are more likely to employ a visual communication directly representing the leader and portraying a positive framework (the image of the smiling leader) with respect to mainstream leaders. Furthermore, right-wing populists prove to be more able than their mainstream counterpart to adjust their communication in relation to the pandemic, showing a rapid decrease of images that show them smiling in the toughest phases of the first wave. The contribution also represents an exercise aimed at showing how machine learning algorithms – and specifically computer vision tools – represent a useful device for studying online communication.
Scaduto, G., Mancosu, M. (2022). CROCODILE TEARS? THE VISUAL CONTENTS ON INSTAGRAM OF POPULIST AND MAINSTREAM POLITICIANS BEFORE AND DURING THE PANDEMIC|Lacrime di coccodrillo? Variazioni nel contenuto visuale su Instagram dei politici populisti e mainstream durante la pandemia. COMUNICAZIONE POLITICA, 23(2), 255-276 [10.3270/104851].
CROCODILE TEARS? THE VISUAL CONTENTS ON INSTAGRAM OF POPULIST AND MAINSTREAM POLITICIANS BEFORE AND DURING THE PANDEMIC|Lacrime di coccodrillo? Variazioni nel contenuto visuale su Instagram dei politici populisti e mainstream durante la pandemia
Scaduto G.
;
2022
Abstract
This contribution aims at investigating the changes in visual communication by Italian political leaders on Instagram during the outbreak of the Covid-19 pandemic. Using a dataset including all the posts published by the main Italian political leaders from September 20th, 2019 to September 20th, 2020 (n = 6,865) and using face and emotional recognition algorithms, we analyze the differences in the visual content proposed by populist and mainstream political actors. Results indicate that populist right leaders (Salvini and Meloni) are more likely to employ a visual communication directly representing the leader and portraying a positive framework (the image of the smiling leader) with respect to mainstream leaders. Furthermore, right-wing populists prove to be more able than their mainstream counterpart to adjust their communication in relation to the pandemic, showing a rapid decrease of images that show them smiling in the toughest phases of the first wave. The contribution also represents an exercise aimed at showing how machine learning algorithms – and specifically computer vision tools – represent a useful device for studying online communication.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.