Social Norms to counteract misinformation in human-AI hybrid systems

The goal of the project is to investigate the role of social norms on misinformation in online communities. This knowledge can help identify new interventions in online communities that help prevent the spread of misinformation. To accomplish the task, the role of norms will be explored by analyzing Twitter data gathered through the Covid19 Infodemics Observatory, an online platform developed to study the relationship between the evolution of the COVID-19 epidemic and the information dynamics on social media. This study can inform a further set of microprojects addressing norms in AI systems through theoretical modelling and social simulations.

Output

Diagnosis and visualization map of existing social norms underlying fake news related to COVID19

Presentations

Project Partners:

• Consiglio Nazionale delle Ricerche (CNR), ISTC: Eugenia Polizzi)
• Fondazione Bruno Kessler (FBK), Marco Pistore

Primary Contact: Eugenia Polizzi, CNR-ISTC

Main results of micro project:

Through the analysis of millions of geolocated tweets collected during the Covid-19 pandemic we were able to identify the existence of structural and functional network features supporting an “illusion of the majority" on Twitter. Our results suggest that the majority of fake (and other) contents related to the pandemic are produced by a minority of users and that there is a structural segmentation in a small “core” of very active users responsible for large amount of fake news and a larger "periphery" that mainly retweets the contents produced by the core. This discrepancy between the size and identity of users involved in the production and diffusion of fake news suggests that a distorted perception of what users believe is the majority opinion may pressure users (especially those in the periphery) to comply with the group norm and further contribute to the spread of misinformation in the network.

Contribution to the objectives of HumaneAI-net WPs

Top-down “debunking” interventions have been applied to limit the spread of fake news, but so far with limited power. Recognizing the role of social norms in the context of misinformation fight may offer a novel approach to solve such a challenge, shifting to bottom-up solutions that help people to correct misperceptions about how widely certain opinions are truly held. The results of this microproject can inform new strategies to improve the quality of debates in online communities and counteract polarization in online communities (WP4). These results can be also relevant for WP2 (T 2.4), e.g., by giving insights about how human interactions can influence and are influenced by AI technology, WP3 (T 3.3) by offering tools to study the reactions of humans within hybrid human-AI systems and WP5 (T 5.4) by evaluating the role of social norms dynamics for a responsible development of AI technology.

Tangible outputs

• Publication: The voice of few, the opinions of many: evidence of social biases in Twitter COVID-19 fake news sharing – Piergiorgio Castioni, Giulia Andrighetto, Riccardo Gallotti, Eugenia Polizzi, Manlio De Domenico
  https://arxiv.org/abs/2112.01304