Improving Language Models for Emotion Analysis: Insights from Cognitive Science (2024)

Abstract: We propose leveraging cognitive science research on emotions and communication to improve language models for emotion analysis. First, we present the main emotion theories in psychology and cognitive science. Then, we introduce the main methods of emotion annotation in natural language processing and their connections to psychological theories. We also present the two main types of analyses of emotional communication in cognitive pragmatics. Finally, based on the cognitive science research presented, we propose directions for improving language models for emotion analysis. We suggest that these research efforts pave the way for constructing new annotation schemes, methods, and a possible benchmark for emotional understanding, considering different facets of human emotion and communication.

## introduction emotion analysis in natural language processing aims to develop computational models capable of discerning human emotions in text. recently, language models have been widely used to solve various tasks in natural language processing, including emotion analysis @xcite . this field of research faces several limitations. first, different ways of conceptualizing emotions lead to different annotation schemes and datasets @xcite . as a result, the generalization ability of models is limited, and it is often impossible to compare studies. to address these limitations, it has been proposed to unify some annotation schemes based on the semantic proximity of emotion categories @xcite , to automatically find emotion categories from data @xcite , or to obtain emotion embeddings independent of annotation schemes @xcite . inspired by psychology and cognitive science research, we believe building an annotation scheme unifying different perspectives on the emotional phenomenon would be possible and desirable. in addition, existing benchmarks evaluate certain aspects of emotional understanding but do not consider its full complexity @xcite @xcite . for example, @xcite proposes to evaluate the emotional understanding of language models by predicting the intensity of emotions in conflict scenes. this type of evaluation is too limited: benchmarks should reflect as much as possible the richness of emotional understanding in humans, a richness documented in different branches of affective sciences @xcite @xcite @xcite . another related research area focuses on the theory of mind of language models, i.e., their ability to correctly attribute mental states to others. in our view, this literature is promising in that it links recent developments in language models to theories and empirical methods in cognitive science (for a review, see bonard (2024, section 5)). notably, several tasks and benchmarks have been developed to measure the ability of language models to succeed at different versions of the false belief task @xcite @xcite @xcite @xcite @xcite . however, theory of mind and, more generally, social reasoning abilities go beyond the ability to succeed at the false belief task @xcite @xcite . the ability to correctly interpret expressed emotions cannot be reduced to it. the degree to which language models possess this emotional competence is worth studying in its own right. generally speaking, research on language mod-els for emotion analysis would benefit from cognitive science research on emotion and communication. in particular, we believe this approach can lead to better ways of annotating emotions expressed in text. additionally, it can improve the evaluation of the emotional understanding of language models by developing new benchmarks. in what follows, we present an overview of psychological theories of emotion (section 2) and ways of annotating emotions in natural language processing (section 3). then, inspired by specific psychological and linguistic theories (section 4), we propose research directions to address some of the current limitations of emotion analysis (section 5). ## emotion theories in cognitive science this section will present the three main emotion theories in psychology to provide a background for connecting emotion analysis in natural language processing with cognitive science. ## emotion analysis in text emotion is a category. textual emotion analysis relies on basic emotion theories to define different emotion categories to associate with textual units (a textual span, a sentence, or a document). for instance, the sentence "i love philosophy." could automatically be associated with the discrete emotion happiness. several annotation schemes focus on subsets of categories while others encompass a broader set, reaching over 28 different categories @xcite . emotion is a continuous value with affective meaning. instead of representing emotion as a category, some annotation schemes consider emotion as a point in a multidimensional space, associating continuous values with textual units @xcite . these dimensions carry an affective meaning. two dimensions dominate the literature and stem from psychological constructivism, which considers, as we have seen, that an emotion can be characterized by its degree of pleasantness and its degree of arousal. thus, the sentence "his voice soothes me." could be automatically associated with two continuous values: a degree of pleasantness of 4 out of 5 and a degree of arousal of 1 out of 5. emotion is a continuous value with cognitive meaning. these dimensions can also carry a cognitive meaning. recently, a new line of research proposes incorporating appraisal theories into emotion analysis models @xcite @xcite . from this perspective, emotions are caused by events evaluated according to several cognitive dimensions. for example, the sentence "i received a surprise gift." could be automatically associated with several continuous values: the event is sudden (4 out of 5), contrary to social norms (0 out of 5), and the person has control over the event (0 out of 5). ## cognitive pragmatics and emotional communication two analyses of communication. cognitive pragmatics is the branch of cognitive science concerned with how agents use and interpret signs in communication. in this and related branches, it is common to distinguish between two broad ways to analyze communication: the "dictionary analysis" (a.k.a. the "code", "semiotic", or "semantic" model) and the "detective analysis" (a.k.a. the "gricean", "inferential", or "pragmatic" model) @xcite @xcite ). ## conclusion emotion analysis has several limitations that, we believe, are partially due to a lack of communication with other disciplines and, in particular, cognitive science. we propose exploiting cognitive science research on emotions and communication to address some limitations, especially what we called "the integrated framework" in emotion theories and "the detective analysis" in cognitive pragmatics. we suggest that this opens the way for constructing new annotation schemes, methods, and benchmarks for emotional understanding that consider the multiple facets of human emotion and communication.