## 5 Experiment Results and Discussion
We also extend our contribution in this work by expanding our criteria in data gathering, meaning that, instead of monitoring specific keywords or hashtags, we take into account unbiased tweets, so we not only can capture how people react to the pandemic but also how they deal with their daily lives in general. Once the necessary operations have been executed, we possess values for the _Emotional Rating, Emotional Impact_, and _Emotional Baseline_; all the ingredients we need to expose our results. Based on these variables, we present our observations as the individual variation of the _degree of Emotional Concern_ as well as the 15 selected moods. In order to follow the evolution of the pandemic, we decided to help ourselves with the data of the accumulated incidence of 14 days of COVID-19 cases and deaths for each country [44], plus their respective response measures [45]. The results obtained in this experiment lead to the conclusion that, for most cities, the onset of the pandemic is received with a clear negative reaction--an increase in moods with a higher rate of displeasure in the Circumplex model \begin{table}
\begin{tabular}{c c} \hline \hline
**Criteria** & **Description** \\ \hline User Activity & \textgreater{}2 tweets/week \\ Account Type & Personal \\ Join Date & \textless{}2017 \\ User Count (per location) & \textgreater{}200 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Criteria for User Capturing and Data Collection. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**English** & **French** & **German** & **Italian** & **Polish** & **Spanish** \\ \hline pandemic & pandemic & Pandemic & pandemia & pandemic & pandemia \\ covid & covid & covid & covid & covid & covid \\ coronavirus & coronavirus & coronavirus & coronavirus & coronavirus & coronavirus & coronavirus \\ lockdown & confinement & Ausgangssperre & confinamento & zakaz wyjšcia & confinamiento \\ quarantine & quarantine & Quarantine & quaranttena & Kwarantanna & cuarenttena \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Top 5 COVID-related search terms. (Figures 5-10), associated with the exponential increase in cases nationwide. The degree of emotional concern (DEC) thus reflects an increase in concern about this growing number of infections. We could speak of a certain causality concerning DEC and the imposition of restrictive countermeasures on social activities and mobility, as a response to the gravity of the situation. At first glance, it is evident that the emotional response is not the same in all countries: we find similarities in Berlin, London, Madrid, and Warsaw (Figures 5-10), where the DEC evolves with a decreasing trend concerning the initial peak, while in Rome and Paris that variation is not so tangible (Figures 8 and 9). As we can see, in every location, we can find a growing trend in the _degree of Emotional Concern_ corresponding to a first reaction. It was on 11 March when WHO declared COVID-19 a global pandemic, and governments started taking action around the same time, impacting the daily lives of the population. This came to be reflected in social interactions, for example, by considering mood variations in Madrid (Figure 11), people are feeling more _nervous_, _tense_, and _upset_ than the previous year. We can find a strong correlation between our results and those resulting from previous studies that concluded an increase in low valence emotions, such as _anger_, _axixous_, or _tense_[46]. However, in all six locations, the DEC begins decreasing after this first peak. We find a steady decrease rate in some cities like Warsaw, where the infection and death rate of the country is much lower than the rest. On the other hand, Rome presents an unstable evolution of the DEC. Focusing again on Madrid, it is noticeable how, given the number of infections and deaths, the DEC still falls significantly after its summit, and even when a new wave of infections begins, the DEC response is not quite the same as in the beginning.