Update README.md

README.md

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 Key features:
 
-- EPIC (English Perspectivist Irony Corpus) is the first annotated corpus specifically created for irony analysis based on the principles of data perspectivism.
-- The corpus contains short social media conversations in five regional varieties of English, annotated by contributors from five countries corresponding to those varieties.
-- The analysis of the resource considers the perspectives of the annotators in terms of origin, age, and gender, and the relationship between these dimensions, irony, and the topics of conversation.
-- To validate EPIC, perspective-aware models are created that encode the perspectives of annotators based on their demographic characteristics.
-- The performance of perspectivist models confirms that different annotators induce very different models.
-- In classifying ironic and non-ironic texts, perspectivist models prove to be generally more confident than non-perspectivist ones.
-- Perspectivist models tend to more accurately detect ironic language, indicating their ability to capture the different perceptions of irony.
-- The models reveal interesting insights about the variation in the perception of irony among different groups of annotators, such as among different generations and nationalities.
-- The EPIC corpus provides a useful resource for training perspective-aware models for irony detection, and highlights the influence of demographic factors on the perception and understanding of irony.
+- EPIC (English Perspectivist Irony Corpus) is an annotated corpus for irony analysis based on data perspectivism principles.
+- The corpus contains social media conversations in five regional varieties of English, annotated by contributors from corresponding countries.
+- The dataset explores the perspectives of annotators, taking into account their origin, age, and gender.
+- Perspective-aware models were created to validate EPIC, and these proved more effective and confident in identifying irony than non-perspectivist models.
+- The models showcase variation in irony perception across different demographic groups.
+- EPIC serves as a valuable resource for training perspective-aware models for irony detection.
 
 Metadata in Creative Language Toolkit ([CLTK](https://github.com/liyucheng09/cltk))
 - CL Type: Irony