Model evaluation for extreme risks T Shevlane, S Farquhar, B Garfinkel, M Phuong, J Whittlestone, J Leung, ... arXiv preprint arXiv:2305.15324, 2023 | 107 | 2023 |
Sociotechnical safety evaluation of generative ai systems L Weidinger, M Rauh, N Marchal, A Manzini, LA Hendricks, ... arXiv preprint arXiv:2310.11986, 2023 | 70 | 2023 |
Polarisation and the Use of Technology in Political Campaigns and Communication N Marchal, LM Neudert Study Panel for the Future of Science and Technology, European Parliamentary …, 2019 | 60* | 2019 |
News and Political Information Consumption in Brazil: Mapping the First Round of the 2018 Brazilian Presidential Election on Twitter C Machado, B Kira, G Hirsch, N Marchal, B Kollanyi, PN Howard, ... Oxford Internet Institute, Data Memo 2018.4, 2018 | 57 | 2018 |
“Be nice or leave me alone”: An intergroup perspective on affective polarization in online political discussions N Marchal Communication Research 49 (3), 376-398, 2022 | 53 | 2022 |
Junk News During the EU Parliamentary Elections: Lessons from a Seven-Language Study of Twitter and Facebook N Marchal, B Kollanyi, LM Neudert, PN Howard Oxford Internet Institute, Data Memo 2019.3, 2019 | 51 | 2019 |
Coronavirus Coverage by State-Backed English-Language News Sources J Bright, H Au, H Bailey, M Elswah, M Schliebs, N Marchal, C Schwieter, ... Oxford Internet Institute, Data Memo 2020.2, 2020 | 39 | 2020 |
Content Moderation as a Political Issue: The Twitter Discourse around Trump’s Ban M Alizadeh, F Gilardi, E Hoes, KJ Klüser, M Kubli, N Marchal University of Zurich, 2021 | 38 | 2021 |
News and Information over Facebook and WhatsApp during the Indian Election Campaign V Narayanan, B Kollanyi, R Hajela, A Barthwal, N Marchal, PN Howard Oxford Internet Institute, Data Memo 2019.2, 2019 | 36 | 2019 |
Coronavirus News and Information on YouTube: A Content Analysis of Popular Search Terms N Marchal, H Au, PN Howard Oxford Internet Institute, Data Memo 2020.3, 2020 | 35* | 2020 |
“Coronavirus EXPLAINED”: YouTube, COVID-19, and the Socio-Technical Mediation of Expertise N Marchal, H Au Social Media+ Society 6 (3), 2056305120948158, 2020 | 34 | 2020 |
Echo Chambers Exist! (But They're Full of Opposing Views) J Bright, N Marchal, B Ganesh, S Rudinac arXiv preprint 2001.1146, 2020 | 33 | 2020 |
Polarization, Partisanship and Junk News Consumption on Social Media during the 2018 US Midterm Elections N Marchal, LM Neudert, B Kollanyi, PN Howard Oxford Internet Institute, Data Memo 2018.5, 2018 | 30 | 2018 |
Investigating Visual Content Shared over Twitter during the 2019 EU Parliamentary Election Campaign N Marchal, LM Neudert, B Kollanyi, PN Howard Media and Communication 9 (1), 158-170, 2021 | 27 | 2021 |
How Do Individuals in a Radical Echo Chamber React to Opposing Views? Evidence from a Content Analysis of Stormfront J Bright, N Marchal, B Ganesh, S Rudinac Human Communication Research 48 (1), 116-145, 2022 | 19 | 2022 |
The Ethics of Advanced AI Assistants I Gabriel, A Manzini, G Keeling, LA Hendricks, V Rieser, H Iqbal, ... arXiv preprint arXiv:2404.16244, 2024 | 17 | 2024 |
Junk News & Information Sharing during the 2019 UK General Election N Marchal, B Kollanyi, LM Neudert, H Au, PN Howard Oxford Internet Institute, Data Memo 2019.5, 2019 | 13 | 2019 |
Coronavirus Coverage by State-Backed English-Language News Sources: Understanding Chinese, Iranian, Russian and Turkish Government Media J Bright, H Au, H Bailey, M Elswah, M Schliebs, N Marchal, C Schwieter, ... University Of Oxford, 1-7, 2020 | 12 | 2020 |
STELA: a community-centred approach to norm elicitation for AI alignment S Bergman, N Marchal, J Mellor, S Mohamed, I Gabriel, W Isaac Scientific Reports 14 (1), 6616, 2024 | 9 | 2024 |
The Paradox of Poor Representation: How Voter–Party Incongruence Curbs Affective Polarisation N Marchal, DS Watson The British Journal of Politics and International Relations, 13691481211048502, 2021 | 9 | 2021 |