E mo T rans KG : An Innovative Emotion Knowledge Graph to Reveal Emotion Transformation (2024)

Abstract: This paper introduces EmoTransKG, an innovative Emotion Knowledge Graph (EKG) that establishes connections and transformations between emotions across diverse open-textual events. Compared to existing EKGs, which primarily focus on linking emotion keywords to related terms or on assigning sentiment dimension ratings to emotion words by humans, EmoTransKG aims to represent the general knowledge involved in emotion transformation. Specifically, in conversations, successive emotions expressed by a single speaker are temporally considered as the head and tail entities, with open-text utterances (events) occurring between them representing the relation. To explore the knowledge of emotion transformations described in EmoTransKG, we develop a Transformer-based translational model called EmoTransNet, which predictively trains tail entities by interpreting the relation as an operation that transforms the source emotion into the target emotion. Particularly, our designed EmoTransNet serves as a plug-in module that seamlessly integrates with any conversational emotion recognition (CER) models for emotion retrofitting. Experimental results on two CER datasets demonstrate that the incorporation of EmoTransNet with baseline models results in substantial improvements, and the qualitative visualization of entities and relations clearly clarify their unique roles in emotion transformations. These experiments confirm the quality and effectiveness of EmoTransKG.

## introduction in recent years, knowledge graphs (kgs) foot_1 , such as wordnet @xcite , google kg @xcite , or conceptnet 5.5 @xcite , [joyful] actually, i'm reading it to the baby. what, you don't think they can hear sounds in there? you're not serious, i mean, you really talk to it? hey, yertle the turtle. a classic. actually, i'm reading it to the baby. what, you don't think they can hear sounds in there? you're not serious, i mean, you really talk to it? hey, yertle the turtle. a classic. ## methodology in this section, we first outline the construction process of emotranskg and its characteristics ( §3.1). next, we present the emotransnet model for training the emotranskg base ( §3.2). finally, we apply the emotransnet for emotion retrofitting in cer ( §3.3). ## conclusion in this paper, we present emotranskg: an emotion knowledge graph. we define basic emotions in conversation transcripts as emotion entities, and extract event sequences between two entities with the same participant as emotion relations. emo-transkg is the first ekg that establishes emotion transformations and connections. we train an emo-transnet model on emotranskg and utilize it for emotion retrofitting in cer, as well as to visualize the roles of entities and relations in emotion transformations, thereby demonstrating the plausibility and effectiveness of emotranskg. currently, we are extending our approach to other conversational resources, such as dailydialog @xcite and meld @xcite , and fusing these emo-transkgs to achieve high coverage of emotion concepts. we also investigate whether emotranskg can offer recommendations for the engineering of emotion-related word embeddings.