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Jonathan Bright
Jonathan Bright
Head of AI for Public Services and Online Safety, Alan Turing Institute. Research Associate, OII
Bestätigte E-Mail-Adresse bei turing.ac.uk
Titel
Zitiert von
Zitiert von
Jahr
Explaining the emergence of political fragmentation on social media: The role of ideology and extremism
J Bright
Journal of Computer-Mediated Communication 23 (1), 17-33, 2018
298*2018
The social news gap: How news reading and news sharing diverge
J Bright
Journal of Communication 66 (3), 343-365, 2016
2902016
Smart Technology and the Emergence of Algorithmic Bureaucracy: Artificial Intelligence in UK Local Authorities
TM Vogl, C Seidelin, B Ganesh, J Bright
Public Administration Review 80, 946-961, 2020
1782020
Does Campaigning on Social Media Make a Difference? Evidence from candidate use of Twitter during the 2015 and 2017 UK Elections
J Bright, S Hale, B Ganesh, A Bulovsky, H Margetts, P Howard
Communication Research 47 (7), 988–1009, 2020
1612020
Countering extremists on social media: Challenges for strategic communication and content moderation
B Ganesh, J Bright
Policy & Internet 12 (1), 6-19, 2020
1082020
Securitisation, terror, and control: towards a theory of the breaking point
J Bright
Review of International Studies 38 (4), 861-879, 2012
1082012
Estimating local commuting patterns from geolocated Twitter data
G McNeill, J Bright, SA Hale
EPJ Data Science 6 (1), 1-16, 2017
792017
Mechachal: Online debates and elections in Ethiopia-from hate speech to engagement in social media
I Gagliardone, M Pohjonen, Z Beyene, A Zerai, G Aynekulu, M Bekalu, ...
Available at SSRN 2831369, 2016
762016
The real component of virtual learning: motivations for face-to-face MOOC meetings in developing and industrialised countries
M Bulger, J Bright, C Cobo
Information, Communication & Society 18 (10), 1200-1216, 2015
732015
The Life and Death of Political News: Measuring the Impact of the Audience Agenda Using Online Data
J Bright, T Nicholls
Social Science Computer Review 32 (2), 170-181, 2014
732014
Wikipedia traffic data and electoral prediction: towards theoretically informed models
T Yasseri, J Bright
EPJ Data Science 5 (22), 2016
712016
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
64*2022
COVID-related misinformation on YouTube: The spread of misinformation videos on social media and the effectiveness of platform policies
A Knuutila, A Herasimenka, H Au, J Bright, R Nielsen, PN Howard
COMPROP Data Memo 6, 1-7, 2020
58*2020
Crowdsourcing for public policy and government
V Lehdonvirta, J Bright
Policy & Internet 7 (3), 263-267, 2015
562015
Public policy in the platform society
V Nash, J Bright, H Margetts, V Lehdonvirta
Policy & Internet 9 (4), 368-373, 2017
542017
The use of social media for research and analysis: a feasibility study
J Bright, S Hale, H Margetts, T Yasseri
DWP Ad-hoc research report 13, 2014
532014
Can electoral popularity be predicted using socially generated big data?
T Yasseri, J Bright
it - Information Technology 56 (5), 246-253, 2014
532014
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
52*2020
Ministerial Importance and Survival in Government: Tough at the Top?
J Bright, H Döring, C Little
West European Politics 38 (3), 441-464, 2015
522015
Artificial intelligence in government: Concepts, standards, and a unified framework
VJ Straub, D Morgan, J Bright, H Margetts
Government Information Quarterly 40 (4), 101881, 2023
512023
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