Climate change and political polarization are two of the twenty-first century’s critical socio-political issues. Here we investigate their intersection by studying the discussion around the United Nations Conference of the Parties on Climate Change (COP) using Twitter data from 2014 to 2021. First, we reveal a large increase in ideological polarization during COP26, following low polarization between COP20 and COP25. Second, we show that this increase is driven by growing right-wing activity, a fourfold increase since COP21 relative to pro-climate groups. Finally, we identify a broad range of ‘climate contrarian’ views during COP26, emphasizing the theme of political hypocrisy as a topic of cross-ideological appeal; contrarian views and accusations of hypocrisy have become key themes in the Twitter climate discussion since 2019. With future climate action reliant on negotiations at COP27 and beyond, our results highlight the importance of monitoring polarization and its impacts in the public climate discourse.

No abstract

No abstract

A 3-uniform hypergraph H consists of a set V of vertices, and E ⊆ V 3 triples. Let a null labelling be an assignment of ±1 to the triples such that each vertex has signed degree equal to zero. Assumed as necessary condition the degree of every vertex of H to be even, the Null Labelling Problem consists in determining whether H has a null labelling. Although the problem is NP-complete, the subclasses where the problem turns out to be polynomially solvable are of interest. In this study we define the notion of 2-intersection graph related to a 3-uniform hypergraph, and we prove that the existence of a Hamiltonian cycle there, is sufficient to obtain a null labelling in the related hypergraph. The proof we propose provides an efficient way of computing the null labelling.

UNSTRUCTURED Social media radically changed how information is consumed and reported and elicited a disintermediated access to an unprecedented amount of content. The world health organization (WHO) coined the term infodemics to identify the information overabundance during an epidemic. Indeed, the spread of inaccurate and misleading information may alter behaviours and complicate crisis management and health responses. This paper addresses information diffusion during the COVID-19 pandemic period with a massive data analysis on YouTube. First, we analyze more than 2M users’ engagement in 13000 videos released by 68 different YouTube channels, with different political bias and fact-checking indexes. We then investigate the relationship between each user’s political preference and her/his consumption of questionable/reliable information. Our results, quantified using information theory measures, provide evidence for the existence of echo chambers across two dimensions represented by the political bias and by the trustworthiness of information channels. Finally, we observe that the echo chamber structure cannot be reproduced after properly randomizing the users’ interaction patterns.