@article{GoebelMunzert, author = {G{\"o}bel, Sascha and Munzert, Simon}, title = {The Comparative Legislators Database}, series = {British Journal of Political Science}, journal = {British Journal of Political Science}, issn = {0007-1234}, doi = {10.1017/S0007123420000897}, abstract = {Knowledge about political representatives' behavior is crucial for a deeper understanding of politics and policy-making processes. Yet resources on legislative elites are scattered, often specialized, limited in scope or not always accessible. This article introduces the Comparative Legislators Database (CLD), which joins micro-data collection efforts on open-collaboration platforms and other sources, and integrates with renowned political science datasets. The CLD includes political, sociodemographic, career, online presence, public attention, and visual information for over 45,000 contemporary and historical politicians from ten countries. The authors provide a straightforward and open-source interface to the database through an R package, offering targeted, fast and analysis-ready access in formats familiar to social scientists and standardized across time and space. The data is verified against human-coded datasets, and its use for investigating legislator prominence and turnover is illustrated. The CLD contributes to a central hub for versatile information about legislators and their behavior, supporting individual-level comparative research over long periods.}, language = {en} } @article{RomanelloNapoliGreenetal., author = {Romanello, Marina and Napoli, Claudia di and Green, Carole and Kennard, Harry and Lampard, Pete and Scamman, Daniel and Walawender, Maria and Ali, Zakari and Ameli, Nadia and Ayeb-Karlsson, Sonja and Beggs, Paul J and Belesova, Kristine and Berrang Ford, Lea and Bowen, Kathryn and Cai, Wenjia and Callaghan, Max and Campbell-Lendrum, Diarmid and Chambers, Jonathan and Cross, Troy J and van Daalen, Kim R and Dalin, Carole and Dasandi, Niheer and Dasgupta, Shouro and Davies, Michael and Dominguez-Salas, Paula and Dubrow, Robert and Ebi, Kristie L and Eckelman, Matthew and Ekins, Paul and Freyberg, Chris and Gasparyan, Olga and Gordon-Strachan, Georgiana and Graham, Hilary and Gunther, Samuel H and Hamilton, Ian and Hang, Yun and H{\"a}nninen, Risto and Hartinger, Stella and He, Kehan and Heidecke, Julian and Hess, Jeremy J and Hsu, Shih-Che and Jamart, Louis and Jankin, Slava and Jay, Ollie and Kelman, Ilan and Kiesewetter, Gregor and Kinney, Patrick and Kniveton, Dominic and Kouznetsov, Rostislav and Larosa, Francesca and Lee, Jason K W and Lemke, Bruno and Liu, Yang and Liu, Zhao and Lott, Melissa and Lotto Batista, Mart{\´i}n and Lowe, Rachel and Odhiambo Sewe, Maquins and Martinez-Urtaza, Jaime and Maslin, Mark and McAllister, Lucy and McMichael, Celia and Mi, Zhifu and Milner, James and Minor, Kelton and Minx, Jan C and Mohajeri, Nahid and Momen, Natalie C and Moradi-Lakeh, Maziar and Morrissey, Karyn and Munzert, Simon and Murray, Kris A and Neville, Tara and Nilsson, Maria and Obradovich, Nick and O'Hare, Megan B and Oliveira, Camile and Oreszczyn, Tadj and Otto, Matthias and Owfi, Fereidoon and Pearman, Olivia and Pega, Frank and Pershing, Andrew and Rabbaniha, Mahnaz and Rickman, Jamie and Robinson, Elizabeth J Z and Rockl{\"o}v, Joacim and Salas, Renee N and Semenza, Jan C and Sherman, Jodi D and Shumake-Guillemot, Joy and Silbert, Grant and Sofiev, Mikhail and Springmann, Marco and Stowell, Jennifer D and Tabatabaei, Meisam and Taylor, Jonathon and Thompson, Ross and Tonne, Cathryn and Treskova, Marina and Trinanes, Joaquin A and Wagner, Fabian and Warnecke, Laura and Whitcombe, Hannah and Winning, Matthew and Wyns, Arthur and Yglesias-Gonz{\´a}lez, Marisol and Zhang, Shihui and Zhang, Ying and Zhu, Qiao and Gong, Peng and Montgomery, Hugh and Costello, Anthony}, title = {The 2023 report of the Lancet Countdown on health and climate change: the imperative for a health-centred response in a world facing irreversible harms}, series = {The Lancet}, volume = {402}, journal = {The Lancet}, number = {10419}, doi = {10.1016/S0140-6736(23)01859-7}, pages = {2346 -- 2394}, language = {en} } @article{StoetzerErfortRajskietal., author = {Stoetzer, Lukas F. and Erfort, Cornelius and Rajski, Hannah and Gschwend, Thomas and Munzert, Simon and Koch, Elias}, title = {An election forecasting model for subnational elections}, series = {Electoral Studies}, volume = {95}, journal = {Electoral Studies}, publisher = {Elsevier BV}, doi = {10.1016/j.electstud.2025.102939}, abstract = {While election forecasts predominantly focus on national contests, many democratic elections take place at the subnational level. Subnational elections pose unique challenges for traditional fundamentals forecasting models due to less available polling data and idiosyncratic subnational politics. In this article, we present and evaluate the performance of Bayesian forecasting models for German state elections from 1990 to 2024. Our forecasts demonstrate high accuracy at lead times of two days, two weeks, and two months, and offer valuable ex-ante predictions for three state elections held in September 2024. These findings underscore the potential for applying election forecasting models effectively to subnational elections.}, language = {en} } @techreport{OswaldMunzert, type = {Working Paper}, author = {Oswald, Lisa and Munzert, Simon}, title = {Exposure to untrustworthy news media then and now: Declining news media quality over 7 years}, publisher = {OSF}, doi = {10.31235/osf.io/5ndjx_v1}, pages = {8}, abstract = {In a rapidly evolving digital media landscape, understanding how exposure to untrustworthy news changes over time is essential for evaluating its potential effects on public attitudes and behavior. However, there is limited evidence on how demand for untrustworthy news develops across longer time frames. Linking web data with surveys, we compare exposure to untrustworthy news sources across demographic and political groups and over a 7-year time frame for two samples of German adults (N = 1,212 in 2017 and N = 436 in 2024). Visits to untrustworthy news sources make up less than 1\% of media diets and are associated with low satisfaction with democracy and a preference for a far-right party. Propensity score matching reveals stability in untrustworthy news exposure, yet a notable decline in the average quality of news diets over 7 years. These results suggest that while untrustworthy news exposure remains limited and stable, a broader erosion in news quality may pose a growing challenge for informed democratic engagement.}, language = {en} } @techreport{HartmannOueslatiStauferetal., type = {Working Paper}, author = {Hartmann, David and Oueslati, Amin and Staufer, Dimitri and Pohlmann, Lena and Munzert, Simon and Heuer, Hendrik}, title = {Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic Variations}, publisher = {arXiv}, doi = {10.48550/arXiv.2503.01623}, pages = {27}, abstract = {Commercial content moderation APIs are marketed as scalable solutions to combat online hate speech. However, the reliance on these APIs risks both silencing legitimate speech, called over-moderation, and failing to protect online platforms from harmful speech, known as under-moderation. To assess such risks, this paper introduces a framework for auditing black-box NLP systems. Using the framework, we systematically evaluate five widely used commercial content moderation APIs. Analyzing five million queries based on four datasets, we find that APIs frequently rely on group identity terms, such as ``black'', to predict hate speech. While OpenAI's and Amazon's services perform slightly better, all providers under-moderate implicit hate speech, which uses codified messages, especially against LGBTQIA+ individuals. Simultaneously, they over-moderate counter-speech, reclaimed slurs and content related to Black, LGBTQIA+, Jewish, and Muslim people. We recommend that API providers offer better guidance on API implementation and threshold setting and more transparency on their APIs' limitations. Warning: This paper contains offensive and hateful terms and concepts. We have chosen to reproduce these terms for reasons of transparency.}, language = {en} } @inproceedings{HartmannOueslatiStauferetal., author = {Hartmann, David and Oueslati, Amin and Staufer, Dimitri and Pohlmann, Lena and Munzert, Simon and Heuer, Hendrik}, title = {Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic Variations}, series = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems}, booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems}, publisher = {ACM}, address = {New York, NY, USA}, doi = {10.1145/3706598.3713998}, pages = {1 -- 26}, abstract = {Commercial content moderation APIs are marketed as scalable solutions to combat online hate speech. However, the reliance on these APIs risks both silencing legitimate speech, called over-moderation, and failing to protect online platforms from harmful speech, known as under-moderation. To assess such risks, this paper introduces a framework for auditing black-box NLP systems. Using the framework, we systematically evaluate five widely used commercial content moderation APIs. Analyzing five million queries based on four datasets, we find that APIs frequently rely on group identity terms, such as "black", to predict hate speech. While OpenAI's and Amazon's services perform slightly better, all providers under-moderate implicit hate speech, which uses codified messages, especially against LGBTQIA+ individuals. Simultaneously, they over-moderate counter-speech, reclaimed slurs and content related to Black, LGBTQIA+, Jewish, and Muslim people. We recommend that API providers offer better guidance on API implementation and threshold setting and more transparency on their APIs' limitations. Warning: This paper contains offensive and hateful terms and concepts. We have chosen to reproduce these terms for reasons of transparency.}, language = {en} } @article{RomanelloWalawenderHsuetal., author = {Romanello, Marina and Walawender, Maria and Hsu, Shih-Che and Moskeland, Annalyse and Palmeiro-Silva, Yasna and Scamman, Daniel and Smallcombe, James W and Abdullah, Sabah and Ades, Melanie and Al-Maruf, Abdullah and Ameli, Nadia and Angelova, Denitsa and Ayeb-Karlsson, Sonja and Ballester, Joan and Basaga{\~n}a, Xavier and Bechara, Hannah and Beggs, Paul J and Cai, Wenjia and Campbell-Lendrum, Diarmid and Charnley, Gina E C and Courtenay, Orin and Cross, Troy J and Dalin, Carole and Dasandi, Niheer and Dasgupta, Shouro and Davies, Michael and Eckelman, Matthew and Freyberg, Chris and Garcia Corral, Paulina and Gasparyan, Olga and Giguere, Joseph and Gordon-Strachan, Georgiana and Gumy, Sophie and Gunther, Samuel H and Hamilton, Ian and Hang, Yun and H{\"a}nninen, Risto and Hartinger, Stella and He, Kehan and Heidecke, Julian and Hess, Jeremy J and Jankin, Slava and Jay, Ollie and Pantera, Dafni Kalatzi and Kelman, Ilan and Kennard, Harry and Kiesewetter, Gregor and Kinney, Patrick and Kniveton, Dominic and Koubi, Vally and Kouznetsov, Rostislav and Lampard, Pete and Lee, Jason K W and Lemke, Bruno and Li, Bo and Linke, Andrew and Liu, Yang and Liu, Zhao and Lowe, Rachel and Ma, Siqi and Mabhaudhi, Tafadzwanashe and Maia, Carla and Markandya, Anil and Martin, Greta and Martinez-Urtaza, Jaime and Maslin, Mark and McAllister, Lucy and McMichael, Celia and Mi, Zhifu and Milner, James and Minor, Kelton and Minx, Jan and Mohajeri, Nahid and Momen, Natalie C and Moradi-Lakeh, Maziar and Morrisey, Karyn and Munzert, Simon and Murray, Kris A and Obradovich, Nick and Orgen, Papa and Otto, Matthias and Owfi, Fereidoon and Pearman, Olivia L and Pega, Frank and Pershing, Andrew J and Pinho-Gomes, Ana-Catarina and Ponmattam, Jamie and Rabbaniha, Mahnaz and Repke, Tim and Roa, Jorge and Robinson, Elizabeth and Rockl{\"o}v, Joacim and Rojas-Rueda, David and Ruiz-Cabrejos, Jorge and Rusticucci, Matilde and Salas, Renee N and San Jos{\´e} Plana, Adri{\`a} and Semenza, Jan C and Sherman, Jodi D and Shumake-Guillemot, Joy and Singh, Pratik and Sj{\"o}din, Henrik and Smith, Matthew R and Sofiev, Mikhail and Sorensen, Cecilia and Springmann, Marco and Stowell, Jennifer D and Tabatabaei, Meisam and Tartarini, Federico and Taylor, Jonathon and Tonne, Cathryn and Treskova, Marina and Trinanes, Joaquin A and Uppstu, Andreas and Valdes-Ortega, Nicolas and Wagner, Fabian and Watts, Nick and Whitcombe, Hannah and Wood, Richard and Yang, Pu and Zhang, Ying and Zhang, Shaohui and Zhang, Chi and Zhang, Shihui and Zhu, Qiao and Gong, Peng and Montgomery, Hugh and Costello, Anthony}, title = {The 2025 report of the Lancet Countdown on health and climate change: climate change action offers a lifeline}, series = {The Lancet}, volume = {406}, journal = {The Lancet}, number = {10521}, publisher = {Elsevier BV}, doi = {10.1016/S0140-6736(25)01919-1}, pages = {2804 -- 2857}, language = {en} }