use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence and indicate if changes were made. The images or other third party material in this book are included in the book's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the book's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Polarization of public opinion is a major issue for societies, as high levels can promote adverse effects such as hostility. The present paper focuses on the polarization of opinions regarding COVID-19 prevention measures in survey data and on Twitter in the German-speaking regions of Germany, Austria, and Switzerland. The level of polarization is measured by dispersion and bimodality in the opinions based on the sentiment in Twitter data and the agreement in the survey data. Our paper, however, goes beyond existing research as we consider data from both sources separately and comparatively. For this purpose, we matched individuals’ survey responses and tweets for those respondents who shared their Twitter account information. The analyses show that vaccination is more polarizing compared to mask wearing and contact tracing in both sources, that polarization of opinions is more pronounced in the survey data compared to the Twitter data, but also that individuals’ opinions about the COVID-19 measures are consistent in both sources. We believe our findings will provide valuable insights for integrating survey data and Twitter data to investigate opinion polarization.

Previous analyses of environmentally conscious intentions showed that the willingness to sacrifice for the environment decreased during the COVID-19 crisis in Austria. There is a large body of empirical research and theoretical models dealing with the explanation of environmental behavior, but these explanations have always been considered in the context of a pandemic-free society. The aim of this research note is therefore to consider the willingness to sacrifice in a crisis period. The data used for the analyses is the Austrian part of the international ‘Values in Crisis’ survey. For this purpose, more than 2000 individuals were surveyed online about their values, social orientations and their current life situation during the first COVID-19 wave (May 2020). Blockwise regression models are used to examine the influence of crisis perceptions, environmental attitudes and values on the willingness to sacrifice for the environment. The analyses show a relatively strong influence of environmental attitudes and values, but also additional effects of concerns about the COVID-19 crisis and especially its economic impact.

This chapter enhances the previous understanding of Energy Lifestyles by identifying groups with distinct patterns of energy behavior across six areas of life. In contrast to most previous studies, the identification of groups is exclusively conducted on the basis of behavior-related data, whereas the characterization of the groups follows in a second step using psychological and socio-demographic variables. This chapter explicitly considers the multidimensionality of behavior and provides a comprehensive overview of different Energy Lifestyles and their potential roles in energy transition. The finding that there are almost no “average users” points out that policy designs must go beyond average figures based on the national emission figures and need to focus on different Energy Lifestyles.

Research on combining social survey responses and social media posts has shown that the willingness to share social media accounts in surveys depends on the mode of the survey and certain socio-demographics of the respondents. We add new insights to this research by demonstrating that the willingness to share their Facebook and Twitter accounts also depends on the respondents' opinions on specific topics. Furthermore, we extend previous research by actually accessing their social media accounts and checking whether survey responses and tweets are coherent. Our analyses indicate that survey respondents who are willing to share their social media accounts hold more positive attitudes toward COVID-19 measures. The same pattern holds true when comparing their sentiments to a larger Twitter collection. Our results highlight another source of sampling bias when combining survey and social media data: a bias due to specific views, which might be related to social desirability.