Abstract:Based on unique international survey data, this book shows us a much needed, and exceptionally detailed, picture of the solidaristic acts and ideas of Europeans in the context of pressing economic, cultural, and political challenges. A timely, insightful, and thought-provoking contribution to our understanding of the viability of solidarity as a cornerstone of social organization in Europe."-Professor Wim van Oorschot, KU Leuven, Belgium "Solidarity in Europe is a timely book. Austerity measures, the inflow of… Show more
“…Over time, however, this form of expressed solidarity became more controversial. On one hand, these findings are in line with survey-based, quantitative research and its rather optimistic overall picture regarding social solidarity in the EU during earlier crises (Baglioni et al, 2019;Gerhards et al, 2019;Koos and Seibel, 2019;Lahusen and Grasso, 2018); on the other hand, results from our correlation analysis suggests that severe strains during crises coincide with increased levels of antisolidarity statements. We conclude that a convergence of opinion (Santhanam et al, 2019) among the European Twitter-using public regarding the target audiences of solidarity, and the limits of European solidarity vs. national interests, is not in sight.…”
Section: Discussionsupporting
confidence: 88%
“…The current state of social science research on European social solidarity poses a puzzle. On the one hand, most survey research paints a rather optimistic view regarding social solidarity in the EU, despite marked cross-national variation (Binner and Scherschel, 2019;Dragolov et al, 2016;Gerhards et al, 2019;Lahusen and Grasso, 2018). On the other hand, the rise of political polarization and Eurosceptic political parties (Baker et al, 2020;Nicoli, 2017) suggests that the opinions, orientations and fears of a potentially growing political minority is underrepresented in this research.…”
Section: Related Workmentioning
confidence: 94%
“…In the social sciences, social solidarity has always been a key topic of intellectual thought and empirical investigation, dating back to seminal thinkers such as Rousseau and Durkheim (Silver, 1994). Whereas earlier empirical research was mostly confined to survey-based (Baglioni et al, 2019;Gerhards et al, 2019;Koos and Seibel, 2019;Lahusen and Grasso, 2018) or qualitative approaches (Franceschelli, 2019;Gómez Garrido et al, 2018;Heimann et al, 2019), computational social science just started tackling concepts as complex as solidarity as part of natural language processing (NLP) approaches (Santhanam et al, 2019).…”
Section: Related Workmentioning
confidence: 99%
“…The preparedness to share one's own resources with others, be that directly by donating money or time in support of others or indirectly by supporting the state to reallocate and redistribute some of the funds gathered through taxes or contributions (Lahusen and Grasso, 2018)…”
Section: A Appendices Guidelinesmentioning
confidence: 99%
“…The concept of a European society and European solidarity (Gerhards et al, 2019), a form of solidarity that goes beyond the nation state, is rather new. European solidarity gained relevance with the rise and expansion of the European Union (EU) and its legislative and administrative power vis-à-vis the EU member states since the 1950s (Baglioni et al, 2019;Gerhards et al, 2019;Koos and Seibel, 2019;Lahusen and Grasso, 2018). After decades of increasing European integration and institutionalization, the EU entered into a continued succession of deep crises, beginning with the European Financial Crisis in 2010 (Gerhards et al, 2019).…”
We introduce the well-established social scientific concept of social solidarity and its contestation, anti-solidarity, as a new problem setting to supervised machine learning in NLP to assess how European solidarity discourses changed before and after the COVID-19 outbreak was declared a global pandemic. To this end, we annotate 2.3k English and German tweets for (anti-)solidarity expressions, utilizing multiple human annotators and two annotation approaches (experts vs. crowds). We use these annotations to train a BERT model with multiple data augmentation strategies. Our augmented BERT model that combines both expert and crowd annotations outperforms the baseline BERT classifier trained with expert annotations only by over 25 points, from 58% macro-F1 to almost 85%. We use this highquality model to automatically label over 270k tweets between September 2019 and December 2020. We then assess the automatically labeled data for how statements related to European (anti-)solidarity discourses developed over time and in relation to one another, before and during the COVID-19 crisis. Our results show that solidarity became increasingly salient and contested during the crisis. While the number of solidarity tweets remained on a higher level and dominated the discourse in the scrutinized time frame, anti-solidarity tweets initially spiked, then decreased to (almost) pre-COVID-19 values before rising to a stable higher level until the end of 2020.
“…Over time, however, this form of expressed solidarity became more controversial. On one hand, these findings are in line with survey-based, quantitative research and its rather optimistic overall picture regarding social solidarity in the EU during earlier crises (Baglioni et al, 2019;Gerhards et al, 2019;Koos and Seibel, 2019;Lahusen and Grasso, 2018); on the other hand, results from our correlation analysis suggests that severe strains during crises coincide with increased levels of antisolidarity statements. We conclude that a convergence of opinion (Santhanam et al, 2019) among the European Twitter-using public regarding the target audiences of solidarity, and the limits of European solidarity vs. national interests, is not in sight.…”
Section: Discussionsupporting
confidence: 88%
“…The current state of social science research on European social solidarity poses a puzzle. On the one hand, most survey research paints a rather optimistic view regarding social solidarity in the EU, despite marked cross-national variation (Binner and Scherschel, 2019;Dragolov et al, 2016;Gerhards et al, 2019;Lahusen and Grasso, 2018). On the other hand, the rise of political polarization and Eurosceptic political parties (Baker et al, 2020;Nicoli, 2017) suggests that the opinions, orientations and fears of a potentially growing political minority is underrepresented in this research.…”
Section: Related Workmentioning
confidence: 94%
“…In the social sciences, social solidarity has always been a key topic of intellectual thought and empirical investigation, dating back to seminal thinkers such as Rousseau and Durkheim (Silver, 1994). Whereas earlier empirical research was mostly confined to survey-based (Baglioni et al, 2019;Gerhards et al, 2019;Koos and Seibel, 2019;Lahusen and Grasso, 2018) or qualitative approaches (Franceschelli, 2019;Gómez Garrido et al, 2018;Heimann et al, 2019), computational social science just started tackling concepts as complex as solidarity as part of natural language processing (NLP) approaches (Santhanam et al, 2019).…”
Section: Related Workmentioning
confidence: 99%
“…The preparedness to share one's own resources with others, be that directly by donating money or time in support of others or indirectly by supporting the state to reallocate and redistribute some of the funds gathered through taxes or contributions (Lahusen and Grasso, 2018)…”
Section: A Appendices Guidelinesmentioning
confidence: 99%
“…The concept of a European society and European solidarity (Gerhards et al, 2019), a form of solidarity that goes beyond the nation state, is rather new. European solidarity gained relevance with the rise and expansion of the European Union (EU) and its legislative and administrative power vis-à-vis the EU member states since the 1950s (Baglioni et al, 2019;Gerhards et al, 2019;Koos and Seibel, 2019;Lahusen and Grasso, 2018). After decades of increasing European integration and institutionalization, the EU entered into a continued succession of deep crises, beginning with the European Financial Crisis in 2010 (Gerhards et al, 2019).…”
We introduce the well-established social scientific concept of social solidarity and its contestation, anti-solidarity, as a new problem setting to supervised machine learning in NLP to assess how European solidarity discourses changed before and after the COVID-19 outbreak was declared a global pandemic. To this end, we annotate 2.3k English and German tweets for (anti-)solidarity expressions, utilizing multiple human annotators and two annotation approaches (experts vs. crowds). We use these annotations to train a BERT model with multiple data augmentation strategies. Our augmented BERT model that combines both expert and crowd annotations outperforms the baseline BERT classifier trained with expert annotations only by over 25 points, from 58% macro-F1 to almost 85%. We use this highquality model to automatically label over 270k tweets between September 2019 and December 2020. We then assess the automatically labeled data for how statements related to European (anti-)solidarity discourses developed over time and in relation to one another, before and during the COVID-19 crisis. Our results show that solidarity became increasingly salient and contested during the crisis. While the number of solidarity tweets remained on a higher level and dominated the discourse in the scrutinized time frame, anti-solidarity tweets initially spiked, then decreased to (almost) pre-COVID-19 values before rising to a stable higher level until the end of 2020.
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