Funding and partners

Funding

The HUN-REN CSS poltextLAB Artificial Intelligence Laboratory is grateful for the financial support of:

HUN-REN Centre for Social Sciences (CSS)
Hungarian Academy of Sciences Centre of Excellence

Hungarian Artificial Intelligence National Laboratory (MILAB)

 

HORIZON 2020 (European Union founding for Research & Innovation): Observatory for Political Texts in European Democracies: A European research infrastructure (grant agreement: 951832).
CLARIN – European Research Infrastructure for Language Resources and Technology
National Research, Development and Innovation Office (NKFIH) 2017-2019: /FK-123907/, 2018-2019: /FK-129018/
 
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János Bolyai Research Scholarship  (Miklós Sebők, 2019-2020)

CSS HAS Incubator program

International Conference Fund of HAS

MTA Lendület “MOMENTUM”

NKFIH Tudományos Mecenatúra pályázat

ECPR Bonus Fund

Research Development Grant

Partnerships

BME Kommunikációs és Média Tanszék
Mesterséges Intelligencia Koalíció
Quantitative Analysis of Textual Data
MTA SZTAKI LPDS
BME Távközlési és Médiainformatikai Tanszék- SmartLab
Pécsi Tudományegyetem Microsoft AI Tudásközpont

Szegedi Tudományegyetem

Z-inspection® initiative

poltextLAB is affiliated with the Z-inspection® initiative.
Z-Inspection® is a holistic process for evaluating the trustworthiness of AI-based technologies at different stages of the AI lifecycle. In particular, it focuses on identifying and discussing ethical issues and tensions through the development of socio-technical scenarios.
The process has been published in the IEEE Transactions on Technology and Society.
Z-Inspection® is distributed under the terms of the Creative Commons License (Attribution-NonCommercial-ShareAlike CC BY-NC-SA).
Z-Inspection® is listed in the new OECD Catalogue of AI Tools & Metrics.
For more information contact poltextlab@poltextlab.com.

As malicious campaigns multiply, the PROMPT (Predictive Research On Misinformation & Propagation Trajectories) pilot project advances the work of the European Narratives Observatory. We analyze vast amounts of textual data to detect malevolent narratives, focussing on three case-studies: the war in Ukraine, LGBTQI+ rights, and the 2024 European elections.

PROMPT uses the power of LLMs combined with dynamic network analysis for the in-depth recognition of formal patterns across media outlets, social networks and Wikipedia, in 8 languages, based on the rhetorical similarities observed qualitatively. With leading AI-scientists, academics and journalists, we’re developing a refined language model, a narrative monitoring dashboard and MOOCs/trainings for civil society activities.

Coordinator contact details:

opsci: martin[at]opsci[dot]ai / jordan[at]opsci[dot]ai

List of participants (organisations):

  • opsci
  • Universita degli Studi di Urbino Carlo Bo
  • HUN-REN Center for Social Sciences
  • Re:Baltica
  • Les Surligneurs
  • Erich Brost Institute for International Journalism
  • Rīga Stradiņš University
  • Wikimedia France
  • Asociația Digital Bridge
  • Orizzonti Politici APS (OriPo or Orizzonti Politici)

Project results can be found here.

PROMPT is a pilot project co-financed by the European Union under Grant Agreement ID LC-0262930