FeelingBlue: A Corpus for Understanding the Emotional Connotation of Color in Context (2023.tacl-1)
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| Challenge: | Experimental results shed light on the emotional connotation of color in context . color is a powerful tool for conveying emotion across cultures . |
| Approach: | They propose a multimodal dataset for exploring the emotional connotation of color as mediated by line, stroke, texture, shape, and language. |
| Outcome: | The proposed model sheds light on the emotional connotation of color in context and the potential for future studies. |
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| Challenge: | Using a linguistic perspective, emotion annotation is considered a difficult task because of the lack of consensus on emotional categories, the fuzziness of boundaries between them or the great variability of emotion expressions types. |
| Approach: | They propose a scheme for emotion annotation and its manual application on a genre-diverse corpus of texts written in french. |
| Outcome: | The proposed method clarifies the main concepts implied by the analysis of emotions as they are expressed in texts and performs a manual annotation campaign on a corpus of 1,594 texts (ca. 515K tokens) of different genres. |
An Emotional Mess! Deciding on a Framework for Building a Dutch Emotion-Annotated Corpus (2020.lrec-1)
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| Challenge: | Existing frameworks for emotion recognition are limited and do not allow for categorical versus dimensional oppositions. |
| Approach: | They propose to use the emotions joy, love, anger, sadness and fear as well as dimensional models to annotate texts from different domains and topics. |
| Outcome: | The proposed frameworks are well-suited to annotate texts from different domains and topics, but the connotation of the labels strongly depends on the origin of the texts. |
Who Feels What and Why? Annotation of a Literature Corpus with Semantic Roles of Emotions (C18-1)
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| Challenge: | Emotion analysis and classification is a challenging task which has been tackled with relatively straight-forward approaches. |
| Approach: | They propose to annotate emotion trigger phrases and entities in the roles of experiencers, targets, and causes of the emotion in literature by Project Gutenberg. |
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An Analysis of Annotated Corpora for Emotion Classification in Text (C18-1)
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| Challenge: | Several datasets have been annotated and published for classification of emotions. |
| Approach: | They aggregated emotion corpora in a common file format with a shared annotation schema . they perform cross-corpus classification experiments to gain insight and a better understanding of differences . |
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Guilt by Association: Emotion Intensities in Lexical Representations (2021.emnlp-main)
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| Challenge: | linguistic models have a higher correlation with human ground truth ratings than labeled data . word vectors have often been evaluated on standard word relatedness benchmarks . |
| Approach: | They propose to use unsupervised, supervised, and finally supervised methods to extract emotional associations from pretrained vectors and models. |
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CARER: Contextualized Affect Representations for Emotion Recognition (D18-1)
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| Challenge: | Existing methods to model emotion-relevant content are based on rule-based and statistics-based approaches. |
| Approach: | They propose a semi-supervised graph-based algorithm to produce rich structural descriptors . they use word embeddings to evaluate the algorithm on emotion recognition tasks . |
| Outcome: | The proposed method outperforms state-of-the-art methods on emotion recognition tasks. |
Construction of a Chinese Corpus for the Analysis of the Emotionality of Metaphorical Expressions (P18-2)
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| Challenge: | a corpus of 5,605 manually annotated sentences in Chinese is described . emotion is an abstract and vague conception, which is often described by metaphor . |
| Approach: | They propose to construct a corpus of metaphors annotated with emotion in Chinese . they use an annotation scheme to include linguistic metaphors, emotional categories and intensity . |
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Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions (L18-1)
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Albert Gatt, Marc Tanti, Adrian Muscat, Patrizia Paggio, Reuben A Farrugia, Claudia Borg, Kenneth P Camilleri, Michael Rosner, Lonneke van der Plas
| Challenge: | a crowdsourcing study has been conducted to generate rich textual descriptions of human faces . the aim is to investigate how users describe images of human face images . |
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| Outcome: | The proposed corpus is based on images taken in the wild and is expected to be large enough to support non-trivial machine learning work on the automated description of faces. |
WikiArt Emotions: An Annotated Dataset of Emotions Evoked by Art (L18-1)
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| Challenge: | a dataset of 4,000 pieces of art has annotations for emotions evoked in the observer . the dataset can help answer questions about what makes art evocative, how does art convey different emotions, what attributes of a painting make it well liked, and how much does the title impact the affectual response to art. |
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PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry (2020.lrec-1)
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| Challenge: | a new study shows that literature enables engagement in a broader range of complex and subtle emotions. |
| Approach: | They propose to use multiple emotion labels to capture mixed emotions in poetry . they evaluate an annotation experiment with experts and crowdsourcing . |
| Outcome: | The proposed method shows that identifying aesthetic emotions is challenging in the German subset. |