Update README.md

README.md

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 ---
 license: mit
+task_categories:
+- text-classification
+language:
+- en
+tags:
+- emotion
+- complexity
+- readability
+- sentiment
+pretty_name: CAMEO
+size_categories:
+- 10K<n<100K
 ---
+# Dataset Card for CAMEO
+
+<!-- Provide a quick summary of the dataset. -->
+
+Dataset to accompany the EMNLP'23 paper titled: "Misery Loves Complexity: Exploring Linguistic Complexity in the Context of Emotion Detection".
+
+## Dataset Details
+
+50,000 subset from the GoEmotions Dataset automatically annotated with the following linguistic complexity measures:
+
+- idt: Incomplete Dependency Theory
+- dlt: Dependency Locality Theory
+- nnd: Nested-Nouns Distance
+- le: Left-embededness
+- percentage_polysyllable_words: % of polysyllable words
+- avg_conn_doc: Average connectives per sentence
+- number_of_uniq_entities: Number of unique named entities
+- average_word_len: Average word length
+- dale_word_frequency_score: DALE Word Frequency Score
+- avgtfidf: Average TF-IDF of all words based on the background corpus
+- avgll: Average Log-likelihood of all words based on the background corpus
+- type_token_ratio_perc: % Type-token ratio
+
+Please refer to the paper for further details on the metrics or other information.
+
+For details on how the data was collected or annotated for emotions. Please refer to the original [GoEmotions dataset](https://github.com/google-research/google-research/tree/master/goemotions).