This article examined the research landscape of energy justice within the social sciences, providing a detailed overview of key developments, trends, and methodologies in this emerging field of study. The study began by identifying the leading journals in the field and mapping co-authorship networks, followed by an analysis of keyword co-occurrences to pinpoint the central themes in the literature. The findings highlight key areas of energy injustice, including accessibility, affordability, and environmental and technological factors. The article further inspected the underlying drivers of these disparities and the actions being taken to address them, emphasizing the critical role of emerging community pressures in shaping policy decisions. Additionally, the study reviewed five case studies that underscore the need for ongoing policy adaptation and illustrate the significant impact of advocacy in the development and implementation of equitable energy policies. The paper concludes by stressing the importance of rethinking current energy policy approaches to create a more inclusive, sustainable, and just energy future.

This study investigates the determinants of corporate climate-related lobbying in Italy, focusing on firm-level factors that influence lobbying expenditures and participation in European climate policy discussions. Given rising pressure from governments and stakeholders for sustainable practices, corporate lobbying plays a crucial role in shaping European climate policies. Using an unbalanced panel dataset of Italian firms from 2011 to 2023, we employ advanced econometric methods and AI-supported textual analysis to explore lobbying dynamics. The findings indicate that firm revenue is a key driver of lobbying intensity, with larger firms investing more in lobbying activities and engaging more frequently in climate-related discussions. Additionally, regional differences and company size significantly affect lobbying behaviors, highlighting the role of financial resources and institutional context in shaping firms' climate policy engagement. In this, the research contributes to the limited EU-focused literature on corporate lobbying, providing valuable insights into Italy's unique lobbying landscape and its implications for climate governance.

Climate policies are a key focus of the European Union's political agenda. Lobbyists aim to exert influence on these policies to advance their interests. This paper uses a panel dataset from 2011 to 2022 of European organizations to investigate the relationship between Climate Policy Uncertainty (CPU) and Lobbying Expenditure (LE). The dataset includes annual observations from organizations across eight European countries, incorporating both microeconomic and macroeconomic factors. The results indicate a positive association between CPU and LE, suggesting that higher levels of CPU are systematically linked to increased lobbying efforts within our sample. This relationship remains robust after addressing potential endogeneity concerns using the Two-Stage Least Squares (2SLS) approach. The effect is particularly pronounced in countries with high GDP or high CO₂ emissions, as well as for organizations with lower participation in European Commission meetings. The study also examined the presence of an exogenous shock, specifically the COVID-19 pandemic. While COVID-19 did not alter the existing relationship between CPU and LE, an analysis focused on the pandemic period revealed a reversal in the relationship. These findings carry important policy implications. Governments should prioritize transparency in lobbying activities and address the regulatory challenges posed by CPU to uphold accountability, balance diverse organizational interests, and safeguard the integrity of climate policymaking.

This study investigates public attitudes toward green hydrogen (GH) by analyzing YouTube comments through sentiment analysis and topic modelling. Unlike previous research that situates hydrogen within broader climate or energy debates and focuses on platforms such as Twitter or Bilibili, this work examines GH as a standalone topic and leverages YouTube's longer, context-rich comments to capture richer public discourse. Comments were collected via the YouTube API (Application Programming Interface) from a curated set of videos and analyzed for sentiment using both the rule-based VADER (Valence Aware Dictionary and sEntiment Reasoner) and the generative model ChatGPT-3.5, enabling a qualitative comparison of their performance. Latent Dirichlet Allocation (LDA) was then applied to identify major discussion themes, which were subsequently linked to sentiment trends. The results indicate that ChatGPT-3.5 outperforms VADER in interpreting sarcasm, slang, emoticons, and mixed sentiments. Topic modelling revealed eight key themes, including skepticism about institutional barriers and costs, optimism regarding GH's role in hard-to-decarbonize sectors, comparisons with nuclear energy and electric vehicles, and concerns about environmental and technical challenges. Overall, the study enhances understanding of online public discourse on GH by demonstrating how advanced sentiment analysis tools, combined with topic modelling, can generate deeper insights to inform strategies that better integrate public perceptions with the economic and policy conditions of GH deployment.