Online-Plattformen haben die politische Diskussion verändert, indem sie einerseits mehr Menschen eine Stimme geben, andererseits aber auch schädliche Inhalte wie Hassreden verbreiten. Diese Inhalte beeinflussen die Gesellschaft und Politik negativ. Das Ziel dieses Projekts ist es, die Qualität der Online-Diskussion zu verbessern, indem sowohl schädliche als auch konstruktive Inhalte untersucht werden. Wir definieren schädliche Inhalte als respektlose und beleidigende Beiträge, die persönliche Angriffe oder diskriminierende Sprache enthalten. Konstruktive Inhalte fördern hingegen positive Diskussionen und demokratische Beteiligung.
Das Projekt verfolgt zwei Hauptziele: die Entwicklung von Methoden zur Erkennung schädlicher und konstruktiver Inhalte sowie die Bewertung der Wirksamkeit von Massnahmen zur Reduzierung schädlicher Inhalte und zur Förderung konstruktiver Dialoge. Unsere Forschung umfasst drei Arbeitsbereiche: die Entwicklung und Messung von Erkennungsmethoden, die Bewertung von Massnahmen gegen schädliche Inhalte und die Untersuchung von Massnahmen zur Förderung konstruktiver Inhalte.
Wir arbeiten mit Schweizer Nachrichtenportalen wie Blick und 20 Minuten zusammen und analysieren Daten von Plattformen wie Twitter und Reddit. Das Projekt adressiert Herausforderungen wie die zuverlässige Inhaltserkennung und den Zugang zu Daten und hat entsprechende Massnahmen zur Risikominderung getroffen. Insgesamt wird unser Projekt wertvolle Erkenntnisse und neue Methoden liefern, um die Online-Diskussion zu verbessern und schädliche Inhalte zu reduzieren. Dies wird Forscher:innen, zivilgesellschaftlichen Gruppen und politischen Entscheidungsträgern helfen.
The attitudes of the population towards (public) regulation are the focus of the present study. It is a follow-up study to the 2016 and 2020 analyses of the attitudes of the Swiss population to public regulation (Höglinger/Widmer 2016; Milic/Widmer 2021) and is again based on a population survey.
Development of a new ensemble classifier that outperforms existing MrP (multilevel regression with poststratification) approaches. This project builds on the prior work (Broniecki et al. 2022, https://www.journals.uchicago.edu/doi/full/10.1086/714777) and will improve upon "autoMrP" (https://cran.r-project.org/web/packages/autoMrP/index.html).
The UZH faculties have taken a variety of measures to reduce flight-related greenhouse gas emissions. These range from quotas, incentive taxes and monitoring to compensation solutions. The evaluation project aims to assess the various measures. Different dimensions are assessed, such as the level of information on the measures, their acceptance, and their effects on the travel behavior and climate awareness of UZH members. The evaluation is based on guided interviews with those responsible for the measures and on the development of impact models for the different measures. Furthermore, the evaluation project is based on an analysis of existing data on the travel behavior of UZH members and on a standardized online survey of UZH members. Finally, the experiences with the implementation of the measures are collected in supplementary interviews. Based on the findings, the project formulates recommendations for the attention of decision makers in the faculties and the UZH. However, the significance of this project extends beyond UZH. It can serve as a model for other educational institutions and organizations pursuing similar emission reduction goals. Finally, the findings obtained in this evaluation project contribute to the scientific debate on the question of the acceptance and effectiveness of corresponding measures.
This project will investigate how technology-supported, large-scale crowd computing approaches can be used to strengthen the functions of democratic consultation and popular initiative procedures—arguably the most impactful participatory mechanisms of direct democracy, as they allow the population to not only strongly influence the outcome of the political process but also to set the agenda (in popular initiatives). Hence, this project will build novel hybrid human-machine systems that cultivate, coordinate, and support participants using coordination technology and artificial intelligence (AI) to support these functions in real world democratic settings. Given that these goals need to combine and advance our understanding regarding the political process, the legal framework, as well as modern technology, this project will combine scientific methods from political science, jurisprudence, AI, and computer-supported cooperative work. The insights of this project may prove to be crucial for a direct democracy like Switzerland, to foster democratic innovation and turn its citizens to even more active, AI-empowered participants in the democratic process—a goal which ultimately ensures democratic stability and our welfare.
To catalyse climate action in Europe to protect public health, our overarching goal is to provide new knowledge, data, and tools on: i) the relationships between changes in environmental hazards caused by climate change, ecosystems, and human health; ii) the health co-benefits of climate action; iii) the role of health evidence in decision making; and iv) the societal implications of climate change for health systems.
Evaluation of a cantonal project that seeks to increase youth political participation among those learning a trade.
The impact of digitalization on politics, the media environment, and democratic processes in Switzerland is potentially far reaching, yet remains poorly understood. Media usage has moved online, political debates are being shaped by online campaigns, and the perception of the importance of data protection has shifted massively, changing people’s attitudes about what services the government or private service providers should offer as evidenced by the recent eID referendum. Studying these kinds of questions systematically requires surveys that specifically track population attitudes and behaviors related to digitalization and its consequences. DigiVox is a national survey panel specifically dedicated to the study of the social, economic, cultural, political and policy implications of digital media and their interplay with technological developments in Switzerland. The project is supported by infrastructure funding of the Digitalisierungsinitiative der Zürcher Hochschulen (DIZH), the UZH Digital Society Initiative (DSI), and the University of Zurich. In addition to a recurring set of questions that we ask on each survey, through a competitive process, scholars have the opportunity to buy space on the instrument to ask their own questions.
The main goal of this project is to gather data that helps us understand the political effects of cash transfers. For this purpose, we designed a survey to be administered in the Brazilian municipality of Maricà. We target Maricà specifically to evaluate a unique policy, the Renda Bàsica de Cidadania (RBC). The RBC is a monthly cash transfer of approx. R$170 (US$31) per person. All households with an income below 3 times the minimum wage (3 × R$ 1100) are eligible. We are specifically interested in how the program changed the citizen-government relationship. On the one hand cash transfers which reduce vulnerability are expected to decrease clientelism on the other hand other corrupt activities may replace clientelism when people have more cash on hand. Importantly, perceptions on corruption in general relate to political participation and public support for democracy, which is historically low in Brazil, especially among the poor and vulnerable. Yet, successful programmatic social policies can raise participation and democratic support. Political effects of cash transfers are generally difficult to estimate, since most transfer programs are transitory not permanent like the RBC. We leverage the the eligibility threshold of the RBC, a quasi-exogenous cut-off, which allows us to apply causal inference methods. Since the RBC is financed through oil royalties our research will be informative for the prominent “resource-curse” literature. In this respect we will be able to provide tangible policy conclusions on whether the RBC is feasible model for spending resource revenues.
India is home to some of the most glaring forms of social, economic and political inequalities. Despite the constitutional commitment to address these inequalities, the inadequate provision of public services in terms of quality, efficiency and scale has led to a lack of even the most basic level of livelihood support, social security and opportunity for large parts of the population. In Delhi, the relatively novel Aam Aadmi Party (AAP) has made public service provision a political priority. This has not only contributed to its electoral success in India’s capital in three consecutive elections, but its “Delhi governance model” is now also a selling point in other states. The wide, cross-class support for the AAP and its public service reforms in Delhi is somewhat puzzling: To date, research on Indian middle classes suggests that firstly, from a self-interested point of view, these groups are often sceptical with regard to the often-low-quality services provided by the public sector and tend to rather “exit” to private provision than use their “voice” to improve public services. Secondly, allyship with lower classes to combat inequality by vying for more redistribution and better public services via a political party has so far been rather unknown in the political arenas of the Indian north. In this project, I explore 1) under which circumstances the middle classes in India support reforms to increase the quality of public service provision, 2) how the distributional effects of increased quality public services materialise across social classes and 3) how this affects the social and political attitudes and behaviours of urban middle-class Indians. To examine these issues in more detail, I will use a mixed-methods approach based on both ethnographic and survey data collection, as well as qualitative and quantitative analysis.