How green is Sentiment Analysis? Environmental Topics in Corpora at the University of Turin
Authors: Cristina Bosco, Muhammad Okky Ibrohim, Valerio Basile, Indra Budi (Università di Torino, langing.ai, University of Indonesia, CRISIS Centro di Ricerca Interuniversitario sui cambiamenti Socio-ecologici e la transizione alla Sostenibilità, 2023)
Topic: Sentiment, Emotion, Irony, Hate

Abstract
Despite the unanimous recognition of the plight associated with environmental phenomena and the proliferation of the discourse about it, there is still little work on these issues in the field of NLP. This paper provides a report on the activities we are carrying on at the University of Turin in the application of Sentiment Analysis to environmental topics. In pursuit of the goal of developing resources and tools specifically designed for addressing the complexity of the ongoing environmental debate, we are currently focused on exploring the language used for green issues and defining some annotation schemes that can describe them at different granularity.

Introduction
It has become increasingly common to apply Sentiment Analysis (SA) and text classification to issues with social impact about which people debate. On the one hand, studying a socially impacting phenomenon from such a computational perspective means creating a precise conceptual and linguistic model, thereby achieving a greater understanding of its characteristics, its dynamics, and, not least, how people perceive it. On the other hand, it is a matter of creating tools that can help policymakers and citizens define strategies to address the problems associated with the phenomenon, bearing in mind that the impact of an intervention depends meaningfully on how it is proposed by governments and political parties and accepted by citizens. Among the issues that have a unique social importance today are certainly those related to the environment in which we live. As far as the emergency related to the environment, at first sight, one cannot but notice that the environmental issues underlie a great complexity. This is due to the mixing of natural and human entities and related interests, such as individuals, public and private organisations on the one side, and climate, animals and plants on the other one. The language used to describe and discuss environmental topics also mirrors this complexity and is featured by a certain degree of specialization. Modelling this reality can be therefore especially complex but also particularly useful because it ultimately allows us to better understand the relationship between humans and the environment and to be more aware of the sensitivity towards the environment which is hidden in us. The characteristics of the discourse about the environment can make especially challenging the classification of opinions expressed about it. We may hypothesize that an accurate annotation of data about environmental topics can be helpful in order to achieve reliable results, e.g., in the detection of the polarity or stance in these texts. According to this hypothesis, we are following two major directions: a) to preliminary analyze the linguistic features of the discourse about the environment carried on in different text genres and b) to design specific annotation schemes that take into account the specific features of these texts and to apply them on selected corpora. The first direction allowed us to better understand the meaning of the wide-spreading discussion about the language used in green communication. This was also useful in preparing the ground for the second direction of research, in which we want to model a specific form of communication about green issues, namely that realized in social media. Notwithstanding the relevance of the topics we are addressing, in agreement with the results of the systematic survey of the studies about SA applied to the environment [1], it can be observed that currently in this research area there is a gap and we want to fill it out. Only a few projects indeed exist, also for English, in which environmental topics are addressed by applying SA and in which only fairly rough techniques were used. In this paper, we describe a variety of experiences carried on at the Department of Computer Science of the University of Turin in the development of corpora and tools for SA applied to environmental topics during the last few years. The paper is organized as follows. The next section briefly surveys previous work related to the application of SA to environmental topics. Section three focuses on the collection of data, while the fourth is about the annotation schemes we adopted. Finally, the last section provides some conclusions and hints about our future works.

Conclusion
This paper presents a report on the activities we are carrying on at the University of Turin in the application of SA to environmental topics. Starting with a linguistic analysis of texts extracted from different genres, we are developing data sets for stance detection, fine-grained structured SA, and sentiment term extraction. Notwithstanding the relevance of these topics, very few applications of textual classification techniques and SA have been developed until now. With our activities, we want to start filling out this gap for Italian and English. Nevertheless, this is only a starting point and in future work we will address a more extended domain of texts, for example, news and interviews, so as to provide a more reliable barometer of sentiments towards climate topics as found in a general audience.