Felix Ettensperger
Biographic Data
| ID | 4168744 |
|---|---|
| NAME | Felix Ettensperger |
| GIVEN NAMES | Felix |
| FAMILY NAME | Ettensperger |
| SIGNATURE | ETTENSPERGER F |
| AFFILIATIONS | University of Freiburg |
| ORCID | 0000-0002-6636-7935 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 20 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 3 |
How to convince in a televised debate
What causes viewers to change their winner perception during a televised debate? The article addresses this question, drawing on a large-N field study of the 2021 chancellor debate in Germany, which contains survey and real-time response data for 4613 participants. Using machine learning techniques, we identify determinants of why participants change their opinion about who is winning the discussion during the debate. Our analysis based on random…
Exploring the conditions for youth representation
Research on the underrepresentation of youth in parliaments has rarely focused on political parties. This is surprising as parties are central in the selection of candidates and therefore should play an important role in determining the demographic composition of elected politicians. We created a data set of party parliamentary groups between 2017 and 2020 and conducted a linear regression as well as a fuzzy set QCA. Building upon previous litera…
Introducing a New Dataset
This research note highlights the underrepresentation of younger people in parliaments across the globe, which has been a persistent issue for decades. We introduce a novel open-access dataset containing information on mean and median age as well as the share of MPs in specific age brackets in party parliamentary groups in lower houses or single chambers of national parliaments. The dataset covers 163 cases from 30 countries and features variable…
Identification of Cross-Country Similarities and Differences in Regulation of Religion Between 2000 and 2014 with Help of Cluster Analysis
Building on previous quantitative and qualitative research on cross-country differences and similarities in regulation of religion, this paper employs data for 2000 and 2014 from the third round of the Religion and the State project and uses various cluster analysis techniques to identify country clusters based on the form in which countries regulate religion. The analysis separates between democratic and authoritarian countries. We further study…
The Relationship Between Poverty and Covid-19 Infection and Case-Fatality Rates in Germany during the First Wave of the Pandemic
The relationship between poverty and the infection and case-fatality rates of COVID-19 has emerged as a controversial but understudied topic. In previous studies and reports from the UK and US evidence emerged that poverty-related indicators had a significant statistical effect on case and mortality rates on district level. For Germany, it has largely been assumed that poverty is an equally relevant factor influencing the transmission rates of th…
Forecasting conflict using a diverse machine-learning ensemble
The article examines the potential of multi-model ensemble learning techniques for conflict research and applies an ensemble averaging framework to the prediction task of the 2020 ViEWS armed conflict forecasting competition. The goal is to predict changes of conflict intensity in fifty-four African countries for 6 months into the future. The presented ensemble combines six individual models, using two tree-based learning algorithms, incorporatin…
Boosting the Understanding and Approval of Anti‐Corona Measures–Reducing Exponential Growth Bias and its Effects through Educational Nudges
One major problem of compliance with anti‐coronavirus measures originates from the so‐called exponential growth bias, i.e. the cognitive distortion of systematically underestimating exponential growth and its consequences. We replicate an Amazon MTurk experiment regarding the spread of SARS‐CoV‐2 that was conducted in the general US population during the first wave of the pandemic in March 2020 dealing with this bias. Using a least‐likely‐design‐…
National internal security policies across Europe – a comparative analysis applying big data clustering techniques
Our contribution examines two questions regarding the internal security policies of 28 European countries: First, the question which different internal security conceptions regarding crime management exist and second, how countries cluster along these conceptions. As data foundation, we use a two-dimensional approach examining the dimensions of capabilities and punitivity with two variables for each. For the dimension of capabilities, we utilize …
Exploring the conditions for youth representation
Research on the underrepresentation of youth in parliaments has rarely focused on political parties. This is surprising as parties are central in the selection of candidates and therefore should play an important role in determining the demographic composition of elected politicians. We created a data set of party parliamentary groups between 2017 and 2020 and conducted a linear regression as well as a fuzzy set QCA. Building upon previous litera…
Identification of Cross-Country Similarities and Differences in Regulation of Religion Between 2000 and 2014 with Help of Cluster Analysis
Building on previous quantitative and qualitative research on cross-country differences and similarities in regulation of religion, this paper employs data for 2000 and 2014 from the third round of the Religion and the State project and uses various cluster analysis techniques to identify country clusters based on the form in which countries regulate religion. The analysis separates between democratic and authoritarian countries. We further study…
Introducing a New Dataset
This research note highlights the underrepresentation of younger people in parliaments across the globe, which has been a persistent issue for decades. We introduce a novel open-access dataset containing information on mean and median age as well as the share of MPs in specific age brackets in party parliamentary groups in lower houses or single chambers of national parliaments. The dataset covers 163 cases from 30 countries and features variable…
Forecasting conflict using a diverse machine-learning ensemble
The article examines the potential of multi-model ensemble learning techniques for conflict research and applies an ensemble averaging framework to the prediction task of the 2020 ViEWS armed conflict forecasting competition. The goal is to predict changes of conflict intensity in fifty-four African countries for 6 months into the future. The presented ensemble combines six individual models, using two tree-based learning algorithms, incorporatin…
Boosting the Understanding and Approval of Anti‐Corona Measures–Reducing Exponential Growth Bias and its Effects through Educational Nudges
One major problem of compliance with anti‐coronavirus measures originates from the so‐called exponential growth bias, i.e. the cognitive distortion of systematically underestimating exponential growth and its consequences. We replicate an Amazon MTurk experiment regarding the spread of SARS‐CoV‐2 that was conducted in the general US population during the first wave of the pandemic in March 2020 dealing with this bias. Using a least‐likely‐design‐…
National internal security policies across Europe – a comparative analysis applying big data clustering techniques
Our contribution examines two questions regarding the internal security policies of 28 European countries: First, the question which different internal security conceptions regarding crime management exist and second, how countries cluster along these conceptions. As data foundation, we use a two-dimensional approach examining the dimensions of capabilities and punitivity with two variables for each. For the dimension of capabilities, we utilize …
National internal security policies across Europe – a comparative analysis applying big data clustering techniques
Our contribution examines two questions regarding the internal security policies of 28 European countries: First, the question which different internal security conceptions regarding crime management exist and second, how countries cluster along these conceptions. As data foundation, we use a two-dimensional approach examining the dimensions of capabilities and punitivity with two variables for each. For the dimension of capabilities, we utilize …
The Relationship Between Poverty and Covid-19 Infection and Case-Fatality Rates in Germany during the First Wave of the Pandemic
The relationship between poverty and the infection and case-fatality rates of COVID-19 has emerged as a controversial but understudied topic. In previous studies and reports from the UK and US evidence emerged that poverty-related indicators had a significant statistical effect on case and mortality rates on district level. For Germany, it has largely been assumed that poverty is an equally relevant factor influencing the transmission rates of th…
Forecasting conflict using a diverse machine-learning ensemble
The article examines the potential of multi-model ensemble learning techniques for conflict research and applies an ensemble averaging framework to the prediction task of the 2020 ViEWS armed conflict forecasting competition. The goal is to predict changes of conflict intensity in fifty-four African countries for 6 months into the future. The presented ensemble combines six individual models, using two tree-based learning algorithms, incorporatin…
Boosting the Understanding and Approval of Anti‐Corona Measures–Reducing Exponential Growth Bias and its Effects through Educational Nudges
One major problem of compliance with anti‐coronavirus measures originates from the so‐called exponential growth bias, i.e. the cognitive distortion of systematically underestimating exponential growth and its consequences. We replicate an Amazon MTurk experiment regarding the spread of SARS‐CoV‐2 that was conducted in the general US population during the first wave of the pandemic in March 2020 dealing with this bias. Using a least‐likely‐design‐…
Identification of Cross-Country Similarities and Differences in Regulation of Religion Between 2000 and 2014 with Help of Cluster Analysis
Building on previous quantitative and qualitative research on cross-country differences and similarities in regulation of religion, this paper employs data for 2000 and 2014 from the third round of the Religion and the State project and uses various cluster analysis techniques to identify country clusters based on the form in which countries regulate religion. The analysis separates between democratic and authoritarian countries. We further study…
How to convince in a televised debate
What causes viewers to change their winner perception during a televised debate? The article addresses this question, drawing on a large-N field study of the 2021 chancellor debate in Germany, which contains survey and real-time response data for 4613 participants. Using machine learning techniques, we identify determinants of why participants change their opinion about who is winning the discussion during the debate. Our analysis based on random…
Exploring the conditions for youth representation
Research on the underrepresentation of youth in parliaments has rarely focused on political parties. This is surprising as parties are central in the selection of candidates and therefore should play an important role in determining the demographic composition of elected politicians. We created a data set of party parliamentary groups between 2017 and 2020 and conducted a linear regression as well as a fuzzy set QCA. Building upon previous litera…
Introducing a New Dataset
This research note highlights the underrepresentation of younger people in parliaments across the globe, which has been a persistent issue for decades. We introduce a novel open-access dataset containing information on mean and median age as well as the share of MPs in specific age brackets in party parliamentary groups in lower houses or single chambers of national parliaments. The dataset covers 163 cases from 30 countries and features variable…
Computer Science (6 works) · Sociology (5 works) · Economics (4 works) · Electoral Systems and Political Participation (4 works) · Law (4 works) · Political science (4 works) · Politics (4 works) · Artificial Intelligence (3 works) · COVID-19 epidemiological studies (3 works) · Demography (3 works)