A text data mining approach to the study of emotions triggered by new advertising formats during the COVID-19 pandemic.

Under the influence of the health emergency triggered by the COVID-19 pandemic, many brands changed their communication strategy and included more or less explicit references to the principles of solidarity and fraternity in their TV commercials to boost the confidence and hope of Italian families during the lockdown. The traditional attitudes of the advertising format, which focused on product characteristics, were relegated to the background in order to reinforce the "brand image" through words, signs, hashtags and music that spread empathetic messages to all those who needed to regain hope and trust in a time of extreme emotional fragility. The objective of this paper is to identify the emotions and brand awareness during the lockdown using text mining techniques by measuring customer sentiment expressed on the Twitter social network. Our proposal starts from an unstructured corpus of 20,982 tweets processed with text data mining techniques to identify patterns and trends in people's posts related to specific hashtags and TV ads produced during the COVID-19 pandemic. The innovations in the brand's advertising among consumers seem to have triggered some sense of appreciation and gratitude, as well as a strong sense of belonging that was not present before, as the TV ads were perceived as a disruptive element in consumers' tweets. Although this effect is clearly documented, in this paper we demonstrate its transitory nature, in the sense that the frequency of occurrence of terms associated with an emotional dimension peaks during the weeks of lockdown, and then gradually decreases.

Neurosensory alterations and Interleukins Cascade in SARS-CoV-2 Infection - Results from a Retrospective Cohort of COVID-19 Inpatients.

OBJECTIVE AND DESIGN: The aim of this study was to relate IL-6 and IL-1ß serum levels with the severity of olfactory disorders and with the type of unperceived odors. MATERIALS AND METHODS: 82 inpatients (45 men aged 62.3 ±14.2 and 37 women aged 57.1± 12.8) with only smell dysfunctions were divided into two groups. The evaluation of the smell disorder was carried out with a questionnaire to define which sensitivity is most compromised in COVID-19 patients. Cytokine levels were measured with chemiluminescence and ELISA assay. Statistical analyses were performed with the Wilcoxon Rank test, Welch's Welch's T-test, and Mann-Whitney test (p <0.05). RESULTS: Statistically significant differences in IL-6 and IL-1 ß levels were found in moderate disease patients when there was an impairment of trigeminal sensitivity (p <0.05) and trigeminal and olfactory sensitivity. CONCLUSIONS: The results obtained showed that in COVID-19 patients the impairment of trigeminal sensitivity in association with olfactory sensitivity was more prevalent in moderate than in mild forms.

A dynamic causal modeling of the second outbreak of COVID-19 in Italy.

While the vaccination campaign against COVID-19 is having its positive impact, we retrospectively analyze the causal impact of some decisions made by the Italian government on the second outbreak of the SARS-CoV-2 pandemic in Italy, when no vaccine was available. First, we analyze the causal impact of reopenings after the first lockdown in 2020. In addition, we also analyze the impact of reopening schools in September 2020. Our results provide an unprecedented opportunity to evaluate the causal relationship between the relaxation of restrictions and the transmission in the community of a highly contagious respiratory virus that causes severe illness in the absence of prophylactic vaccination programs. We present a purely data-analytic approach based on a Bayesian methodology and discuss possible interpretations of the results obtained and implications for policy makers.

A dynamic causal modeling of the second outbreak of COVID-19 in Italy

While the vaccination campaign against COVID-19 is having its positive impact, we retrospectively analyze the causal impact of some decisions made by the Italian government on the second outbreak of the SARS-CoV-2 pandemic in Italy, when no vaccine was available. First, we analyze the causal impact of reopenings after the first lockdown in 2020. In addition, we also analyze the impact of reopening schools in September 2020. Our results provide an unprecedented opportunity to evaluate the causal relationship between the relaxation of restrictions and the transmission in the community of a highly contagious respiratory virus that causes severe illness in the absence of prophylactic vaccination programs. We present a purely data-analytic approach based on a Bayesian methodology and discuss possible interpretations of the results obtained and implications for policy makers.