Analyzing the Online Communication of Environmental Movement Organizations: NLP Approaches to Topics, Sentiment, and Emotions (2025)

Abstract: This project employs state-of-the-art Natural Language Processing (NLP) techniques to analyze the online communication of international Environmental Movement Organizations (EMOs). First, we introduce our overall EMO dataset and describe it through topic modeling. Second, we evaluate current sentiment and emotion classification models for our specific dataset. Third, as we are currently in our annotation process, we evaluate our current progress and issues to determine the most effective approach for creating a high-quality annotated dataset that captures the nuances of EMO communication. Finally, we emphasize the need for domain-specific datasets and tailored NLP tools and suggest refinements for our annotation process moving forward.

## introduction in order to address the escalating environmental crises of our time, it is imperative that individuals and groups worldwide act in a collective manner. investigating current environmental movements is crucial as they play a significant role in motivating collective environmental action, shaping public opinion, and influencing policy decisions. the online communication of environmental movement organizations (emos) provides valuable insights into their strategic approaches, thematic content and emotional appeals @xcite . concurrently, the success of these organizations can be ascertained through the examination of various reactions of other users, such as likes and comments. therefore, the objective of our project is to analyze four years of x (former twitter) data, which we refer to as tweets, from a range of international emos, including greenpeace, friends of the earth, fridays for future, extinction rebellion, and climate action network (can) in order to gain a deeper understanding of their communication. we intend to assess the sentiment and emotions conveyed in the emos' language, utilizing and evaluating state-of-the-art natural language processing (nlp) models. as part of this research, our ultimate goal is to create a comprehensive and annotated dataset tailored to climate-and environment-specific content, in the future. in this paper, we present an interim stage of our project, focusing on a critical assessment of our current annotation process to refine and enhance its robustness, with the goal of creating a high-quality annotated dataset. the paper is structured as follows: first, we review related work and outline our research questions. next, we describe our methodology, including the annotation process and the evaluation of existing sentiment and emotion models. we then present our results, highlighting key findings and insights gained from this evaluation. finally, we conclude by discussing the limitations of our approach and proposing avenues for future research, including further dataset development and model fine-tuning for climateand environment-related communication. ## conclusion and future work despite these limitations, our findings provide valuable insights into the strategic communication of emos and the challenges associated with annotating data as well as applying current nlp models to climate-and environmentrelated group discourse. our study underscores the need for handling disagreement in data annotation, domain-specific datasets, and models to address the unique challenges posed by analyzing climateand environment-related content. our preliminary evaluation of the annotation process serves as a crucial step towards refining and enhancing its robustness. it is imperative that future efforts dedicate greater attention to the resolution of disagreement in climate-and environment-related text annotations. overall, future research should prioritize the development of robust domain-specific datasets and the fine-tuning of models to improve accuracy and interpretability. additionally, exploring other psychological constructs, such as efficacy beliefs, alongside traditional sentiment and emotion analysis, should provide a more comprehensive understanding of online climate and environment communication. expanding beyond the current focus on sentiment, emotion, and hate speech to include such constructs can yield a richer and more nuanced perspective on emo strategies and their impact on public discourse.