The I in Misinformation: Understanding the Role of Individual Behavior in Social Media Information Diffusion

Informazioni relative al progetto

URIBMD

ID dell’accordo di sovvenzione: 101111447

DOI 10.3030/101111447

Data della firma CE 13 Luglio 2023

Data di avvio 15 Agosto 2024

Data di completamento 14 Agosto 2026

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale Nessun dato

Contributo UE € 189 687,36

Coordinato da

MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Germania

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documenti, relazioni (1)

Data Management Plan

The project will involve the collection and analysis of multiple forms of data, such as visual attention data, publicly available Twitter data, digital trace data, and quantitative-qualitative data (captured through surveys and interviews). Visual attention data will be captured through the Tobii Eye Tracker, which is a commonly used scientific tool and is already available with the host institution. Twitter data will be collected through the Twitter API, or through open-source web scrapers/packages like ‘snscrape’, and ‘beautiful soup’. Digital trace data will be acquired from the EU-based service ‘Wakoopa’, which works in compliance with GDPR guidelines. Finally, quantitative-qualitative data will be captured through interviews and surveys that will be conducted as part of this work. The captured data will be cleaned and analysed based on state-of-the-art methods published in scientific literature. Once the data has been cleaned and analysed, it will be reviewed and anonymized, before it is uploaded to GitHub and the Open Science Framework (OSF) platform. All generated and collected data will be managed in line with the FAIR principles (Findable, Accessible, Interoperable, Reusable) and documentation on how to find, access, interoperate and reuse the data will be uploaded (in CSV, JSON, or TXT format) on OSF and GitHub to ensure reproducibility. Finally, the corresponding code for analysing the data will also be made available in the public domain (for example via. GitHub), under permissive licenses (such as MIT or CC). A copy of data and code will also be archived at the host institution’s local servers with exclusive access.