ABSTRACT
Music listening choices are considered to be a factor capable of measuring people's emotions. Thanks to the explosion of streaming music applications in recent years, it is possible to describe listening trends of the global population based on emotional features. In this paper we have analysed the most popular songs from 52 countries on Spotify through their features of danceability, positivity and intensity. This analysis allows exploring how these song features reflect mood trends along with other contextual factors that may affect the population's listening behaviour, such as the weather or the influence of the COVID-19 pandemic. Finally, we have proposed a multivariate time series model to predict the preferred type of music in those countries based on their previous music listening patterns and the contextual factors. The results show some relevant behavioural changes in these patterns due to the effect of the pandemic. Furthermore, the resulting prediction model enables forecasting the type of music listened to in three different groups of countries in the next 4 months with an error around 1%. These results may help to better understand streaming music consumption in businesses related to the music and marketing industry. © 2022 Elsevier B.V.
ABSTRACT
Music listening choices are considered to be a factor capable of measuring people’s emotions. Thanks to the explosion of streaming music applications in recent years, it is possible to describe listening trends of the global population based on emotional features. In this paper we have analysed the most popular songs from 52 countries on Spotify through their features of danceability, positivity and intensity. This analysis allows exploring how these song features reflect mood trends along with other contextual factors that may affect the population’s listening behaviour, such as the weather or the influence of the COVID-19 pandemic. Finally, we have proposed a multivariate time series model to predict the preferred type of music in those countries based on their previous music listening patterns and the contextual factors. The results show some relevant behavioural changes in these patterns due to the effect of the pandemic. Furthermore, the resulting prediction model enables forecasting the type of music listened to in three different groups of countries in the next 4 months with an error around 1%. These results may help to better understand streaming music consumption in businesses related to the music and marketing industry.
ABSTRACT
Compared to the spring, when the Covid-19 pandemic started and people honestly followed the precautionary measures, the behavior of the Latvian population has changed significantly. The majority of Latvians do not exercise caution, and their activity has returned to pre-Covid-19 levels this autumn, negatively affecting the epidemiological situation in the country, according to an analysis of population behavior. Within the research, the epidemiological statistics of Center for Disease Prevention and Control and Latvian Mobile Telephone (LMT) mobile network events were analyzed to determine the relationship between population activity and epidemiological situation in Latvia as a whole, as well as in each region. According to the performed analysis, it is possible to divide Latvia into two parts - municipalities that were active during the emergency situation and places where the greatest activity is observed before and after the emergency situation. It was concluded that mobile call activity during emergencies in both cities and counties is still high, it is 70% - 80% of the precrisis period. Since the spring, people's behavior and habits have changed significantly, so a different approach is needed.
ABSTRACT
Large reductions in emergency department attendances and hospitalisations with non-COVID acute medical illness early during the pandemic were attributed to reluctance to seek medical help and higher referral thresholds. Here, we compare acute medical admissions with a comparison cohort from 2017. Deaths in the same geographic area were examined, and Wales-wide deaths during these 4 weeks in 2020 were compared with a seasonally matched period in 2019. There were 528 patients admitted with non-COVID illness in 2020, versus 924 in 2017 (a reduction of 43%). Deaths from non-COVID causes increased by 10.9% compared with 2017, over half this rise being from neurological causes including stroke and dementia. While far fewer patients required hospitalisation as medical emergencies, rises in local non-COVID deaths proved small. Wales-wide non-COVID deaths rose by just 1% compared with 2019. The findings suggest that changes in population behaviour and lifestyle during lockdown brought about unforeseen health benefits.