The digital age has witnessed a surge in disinformation, exacerbated by poor public communication. Social media, now a crucial tool for political leaders, allows anyone to create and disseminate political content globally. The 2022 Italian election campaign saw significant discussion around "nuclear," encompassing both civilian nuclear energy and the fear of atomic conflict in Ukraine. This study examines the social media discourse surrounding these two distinct aspects of the "nuclear" debate. The use of the term "nuclear" was substantial, indicated by Google Trends data showing search volume comparable to that of "immigration." Google News data revealed more than 1,500 related news articles during the three-month campaign. The debate regarding civilian nuclear energy began in late 2021 with the inclusion of nuclear power and gas in the European Taxonomy for Sustainable Activities. This sparked discussion in specialized publications before gaining attention in national newspapers. The European Commission's inclusion of gas and nuclear energy as sustainable sources in February 2022 further fueled the debate. Italy has a complex history with nuclear energy, with two referendums resulting in the rejection of nuclear plants. Existing literature largely focuses on the energy and environmental aspects or examines media coverage following the Chernobyl and Fukushima disasters. The atomic conflict narrative emerged alongside the Russo-Ukrainian War, prompting discussions among political actors and the public about the potential for nuclear escalation. Experts have offered varying perspectives on the likelihood of atomic conflict, with some emphasizing the deterrent effect of existing nuclear arsenals and others raising concerns about the possibility of using tactical nuclear weapons. The geopolitical situation undeniably shaped the public perception of nuclear power. Existing research on social media discussions about nuclear issues, primarily focusing on the post-Fukushima debate in Japan, often relies on text analysis and mainly uses Twitter data. However, the limitations of Twitter data as a sole source for representing public opinion are acknowledged, considering its user base is not entirely representative of the broader population and is influenced by political actors. To overcome these limitations, this research adopts a multiplatform approach incorporating Twitter, Facebook, and Instagram, while acknowledging that insights from one platform can be applied to others sharing similar affordances. The study employs the concept of "Bridges" from transmedia theory to explore cross-platform dynamics and analyze how users connect different social media platforms, creating a personalized social media ecology. The research aims to understand the spread of disinformation within this ecosystem during the Italian electoral campaign, particularly focusing on nuclear themes. Disinformation is defined broadly as any online information potentially leading to a factually incorrect worldview. The study seeks to answer two research questions: 1) What kind of content regarding the nuclear debate was disseminated across platforms through Bridges, and for what purpose? 2) What was the role of Bridges in the spread of disinformation concerning nuclear energy and atomic conflict within the social media ecosystem?

Existing research highlights the manipulation of public opinion through disinformation and conspiracy theories, especially amplified in the digital age. Social media's transformative influence on the media landscape has been widely documented, along with the increased role of ordinary citizens in shaping the information ecosystem. The term "fake news" has become commonplace, referring to fabricated stories spread to fuel propaganda or gain from virality. Studies have noted the rise of political polarization and the contribution of hyper-partisan media to the spread of disinformation, posing a threat to democratic processes. Research focusing on the Italian relationship with nuclear energy has concentrated on energy and environmental perspectives, often analyzing media discourse surrounding major nuclear accidents like Chernobyl and Fukushima. Existing research analyzing social media discussions of nuclear issues often utilizes text analysis on platforms like Twitter and primarily examines data from post-Fukushima Japan. While Twitter has been extensively studied in relation to its impact on society, politics, and public opinion, its limitations in representing the general population and its susceptibility to influence by political actors have also been noted. This research acknowledges these limitations and adopts a multiplatform approach, incorporating Twitter, Facebook, and Instagram, and drawing on transmedia theory to understand cross-platform dynamics. The concept of "Bridges" is introduced to analyze how users connect different platforms within their customized social media ecology.

This research uses a sequential explanatory design, combining quantitative and qualitative methods to analyze the spread of disinformation related to nuclear energy and atomic conflict during the 2022 Italian election campaign on social media. The study focuses on identifying and characterizing "Bridges," defined as narrative connections between different social media platforms. The quantitative phase uses digital methods to collect and process data from Twitter, Facebook, and Instagram, identifying hyperlinks as Bridges. Data from Twitter was collected using 4CAT and data from Facebook and Instagram was collected using CrowdTangle. The pre-processing phase involved filtering the data to select only posts containing URLs linking to other social media platforms. The qualitative phase involved manually exploring the content of the identified Bridges, analyzing the type of content, destination platform, user category, topic, and position. The data was enriched with additional information regarding content type, destination platform, account name, user category (politician, news outlet, activist, etc.), topic (nuclear energy, atomic conflict), and position (pro-nuclear, anti-nuclear, pro-Russia, anti-NATO, etc.). These elements were then classified hierarchically to aid in qualitative analysis. The categorization of disinformation included unverified information, rumors, propaganda, hyper-partisan content, fake news, and conspiracy theories. This qualitative exploration provided insight into the nuanced aspects of the debate and the diverse viewpoints among internet users. Finally, the data was visualized using Cortext and Gephi to map the relationships between users and platforms. The query design involved two queries, one focusing on nuclear-related terms and the other on Italian electoral terms. The intersection of these queries ensured that only the relevant content was selected for analysis. The research also considered the "Trench Warfare Dynamic" model of online discussions, acknowledging the unique characteristics and affordances of each social media platform and how they influence user interactions. Data collection methodologies differed across platforms, reflecting platform-specific functionalities and access limitations. For example, Meta’s data access was restricted to public content from verified accounts, public pages, and public groups, unlike Twitter’s more open API.

The analysis identified 660 Bridges across Twitter, Facebook, and Instagram, linking to various secondary platforms, including YouTube, LinkedIn, Mastodon, Telegram, etc. Analysis of Twitter Bridges showed Facebook and YouTube as the primary destinations. Facebook Bridges were more widely dispersed among various platforms, including YouTube, Instagram, and Telegram. Instagram Bridges, identified through "link in bio" descriptions, primarily connected to the users' accounts on other platforms. Regarding the nuclear energy debate, political actors and activists dominated the discussions on mainstream platforms. The pro-nuclear energy side employed affective language, comparing environmentalists to the Taliban. The anti-nuclear side responded with accusations of misinformation and calls for public debate. Bridges to below-the-radar platforms like Mastodon revealed highly polarized discussions, creating echo chambers. YouTube content often focused on geopolitical news, rumors, and commentary, including channels with pro-Russia and anti-NATO viewpoints. Disinformation, including conspiracy theories and hyper-partisan content, was frequently observed across platforms. Platforms such as Rumble and Bitchute were used as alternatives to YouTube for content removed due to policy violations. Telegram emerged as a key platform for spreading misinformation, with anonymous channels disseminating unverified information and rumors. The study found that Bridges often served a dual purpose: disseminating information and directing users toward favorable environments (echo chambers). Content was characterized as affective (emotional appeals), defective (biased/false information), and potentially infective (viral potential). Below-the-radar platforms facilitated the spread of misleading information, often presenting themselves as uncensored sources. The analysis reveals a complex ecosystem where misinformation is strategically disseminated across various platforms to achieve communicative goals, including presenting alternative perspectives and creating favorable online environments.

The findings address the research questions by revealing the prevalence of affective, defective, and infective content spread through Bridges during the 2022 Italian election campaign. The use of emotional appeals and fear-mongering, along with the dissemination of biased and false information, characterized the online discourse surrounding nuclear energy and the atomic conflict. The strategic use of Bridges to steer users toward echo chambers on below-the-radar platforms amplified the spread of disinformation. The study highlights the interconnected nature of mainstream and fringe platforms within a complex social media ecosystem. This research underscores the need for multiplatform approaches to understand and mitigate disinformation. The observed strategies are not unique to this specific context, suggesting broader implications for understanding online political communication. The results point to the necessity of regulating fringe platforms before they gain mainstream traction.

This study demonstrates the multifaceted nature of disinformation spread across social media during the 2022 Italian elections, focusing on the nuclear debate. The concept of "Bridges" provides a valuable framework for understanding cross-platform dynamics. The identification of affective, defective, and infective content highlights the need for interdisciplinary approaches to counter disinformation. Future research could explore the effectiveness of different strategies to combat disinformation across various platforms, paying particular attention to below-the-radar platforms.

The study's limitations include restricted access to Facebook and Instagram data due to platform policies, limiting the scope of the analysis. The reliance on publicly available data may not fully capture the nuances of private conversations or closed groups. Challenges in analyzing audiovisual content on Instagram also impacted the depth of the analysis. The changing policies on Instagram regarding video length also posed a challenge. Furthermore, the study’s findings are specific to the 2022 Italian electoral context and may not be fully generalizable to other countries or campaigns.