Annotating candy speech in G erman Y ou T ube comments (2025)

Abstract: We describe the phenomenon of candy speech – positive emotional speech in online communication – and introduce a classification of its various types based on the theoretical framework of social interaction by Goffman (1967). We provide a dataset of 46,286 German YouTube comments manually annotated with candy speech

## introduction the theoretical framework of social interaction introduced by @xcite is centered around face-work, where face represents a 'positive social value a person effectively claims for [themselves] [. . . ] an image of self delineated in terms of approved social attributes' (p. 5). in this approach, social interactions involve emotionally charged linguistic utterances which directly influence a person's image or face. @xcite assumes various states and processes related to face: an individual is said to be 'in face' when they feel confident and assured, hence one strives to 'maintain one's face', i.e., to sustain a positive image of oneself. at the same time, one fears to 'lose face', which could result in a damage to one's image. in cooperative discourse, mutual face support is desired and even expected, and, if heeded, ensures that faces are maintained. furthermore, 'face-saving' and 'face-giving' strategies can be applied when face is lost. the former allows an individual to sustain an impression that they have not lost their face, while the latter refers to the process by which others help an individual to 'gain face'. in linguistics, face-work plays a central role, as it provides insight into how language functions not only as a medium for conveying information, but also as a means to manage social relationships, shape interpersonal dynamics, and construct identities in interactions. nonetheless, very few studies have addressed positive interactions in social media from a corpus-based perspective via annotation of significant amounts of realistic data or using computational approaches. annotation efforts have so far centered on negative online interactions, and linguistic expressions that negatively influence another person's or group's public image have been extensively studied. the area of negative communication practices has been delineated in great detail, with distinctions between hate speech, offensive language, toxicity, and many other subtypes (see @xcite , for a survey, and references therein). in contrast, little empirical work has been done on the positive side, despite the fact that (as we believe) positive face-work is similarly complex, and despite the fact that positive social engagement leads many users to strongly associate with certain virtual communities and spend large amounts of time interacting online. the lack of empirical research on positive face-work means that we know very little on how it looks and how to identify it in online data. studying the types of phenomena that make up positive interactions in digital media may enable us to automatically find and possibly enhance positive face-work, and may help us understand how virtual communities and identities are constructed through language. in this study, we focus on candy speech -a term we use for positive face-work in online discourse that provides face support for others. we develop a classification of candy speech types that allows for a differentiated view of face-supporting strategies. some previous work has already documented the prevalence of (certain types of) positive speech in social media (e.g., chakravarthi and muralidaran 2021; jiménez-zafra et al. 2023 on 'hope speech' or @xcite on 'empowerment language'). face-work, in particular positive face-work, has however rarely been directly addressed in corpus or computational linguistic studies (but see @xcite @xcite . specifically, @xcite work on small talk in task-oriented dialogs, which she frames in face-work terms, is relevant for our study. @xcite develops a taxonomy of dialog acts for non-task-oriented passages in virtual reality dialogs based on the notion that these interactions typically serve social purposes: to either request support for one's own face, or to provide face support for the interlocutor. in our classification of candy speech, we build on and extend klüwer's face supporting dialog acts based on social media interactions between real humans. our main contributions are the following: ## dataset we work with the data from the nottdeuytsch corpus @xcite , which contains over 33 million words taken from approximately 3 million youtube comments published between 2008 and 2018 by a young german-speaking audience. comments posted on social media platforms often represent emotional discourse. in addition, it is known that youtube comments in particular contain many positive social interactions, for example within fan groups and other communities @xcite , thus being suitable for our purposes. we selected 16 videos authored by seven creators, together with all their comments. to reflect the topic distribution in the original corpus, the creators/videos were selected randomly; however, we made sure that the creators represent different sectors (e.g., music, tutorials) so that the commenting communities can be expected to differ in the frequency and types of candy speech expressions. the annotated dataset consists of a total of 46,286 comments, grouped into 16 'documents' according to the video they relate to. foot_0 3 candy speech 3.1 definition following goffman's (1967) theory, we define candy speech as face-support that aims to help others maintain and restore their positive (self-)image. candy speech thus is constituted by expressions of positive attitudes and feelings on social media towards individuals (e.g., content creators or commenters) and their posts @xcite . the purpose of candy speech is to encourage, cheer up, support or empower others. candy speech can be viewed as the counterpart to hate speech, as it likewise aims to influence the self-image of the target person or group, but in a positive way. in the following section, we describe our classification of candy speech expressions against the backdrop of face-work strategies. ## conclusion and discussion this study contributes to the identification and promotion of positive online discourse. we have defined the phenomenon of candy speech as positive face-work in online communication and provided a detailed annotation scheme for its different types. further, we discussed challenges related to the annotation and evaluation of this type of span-based semantic properties. our work facilitates a deeper understanding of positive face-work in online settings by showing that candy speech varies across several dimensions: its 'target' (e.g., an individual or their output), the domain/topic of the creator/video (e.g., expressions of gratitude are most common with videos offering practical advice), and the level of intensity (e.g., affection declaration may reflect stronger emotions than compliments or positive feedback). empirical research into candy speech and its linguistic realizations can yield insights into how virtual communities constitute themselves and support each other. the dataset we provide can be used to train computational models to detect (and potentially generate) various types of candy speech, and positive language more broadly, e.g., for mitigating face threats. as the next step, we plan to look into a finergrained differentiation of our majority class positive feedback as well as of the reactive comments with respect to face-supporting and face-saving acts.