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Update files from the datasets library (from 1.2.0)

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Release notes: https://github.com/huggingface/datasets/releases/tag/1.2.0

Files changed (5) hide show
  1. .gitattributes +27 -0
  2. README.md +165 -0
  3. dataset_infos.json +1 -0
  4. dummy/0.0.0/dummy_data.zip +3 -0
  5. emotone_ar.py +78 -0
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.bin filter=lfs diff=lfs merge=lfs -text
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+ *.bin.* filter=lfs diff=lfs merge=lfs -text
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+ *.bz2 filter=lfs diff=lfs merge=lfs -text
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+ *.ftz filter=lfs diff=lfs merge=lfs -text
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+ *.gz filter=lfs diff=lfs merge=lfs -text
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+ *.joblib filter=lfs diff=lfs merge=lfs -text
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+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.msgpack filter=lfs diff=lfs merge=lfs -text
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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README.md ADDED
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+ ---
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+ annotations_creators:
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+ - found
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+ language_creators:
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+ - found
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+ languages:
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+ - ar
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+ licenses:
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+ - unknown
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+ multilinguality:
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+ - monolingual
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+ size_categories:
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+ - 1k<n<10k
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+ source_datasets:
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+ - original
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+ task_categories:
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+ - text_classification
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+ task_ids:
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+ - emotion-classification
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+ ---
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+
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+ # Dataset Card for MetRec
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+
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+ ## Table of Contents
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+ - [Dataset Description](#dataset-description)
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+ - [Dataset Summary](#dataset-summary)
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+ - [Supported Tasks](#supported-tasks-and-leaderboards)
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+ - [Languages](#languages)
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+ - [Dataset Structure](#dataset-structure)
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+ - [Data Instances](#data-instances)
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+ - [Data Fields](#data-instances)
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+ - [Data Splits](#data-instances)
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+ - [Dataset Creation](#dataset-creation)
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+ - [Curation Rationale](#curation-rationale)
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+ - [Source Data](#source-data)
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+ - [Annotations](#annotations)
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+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
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+ - [Considerations for Using the Data](#considerations-for-using-the-data)
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+ - [Discussion of Social Impact and Biases](#discussion-of-social-impact-and-biases)
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+ - [Other Known Limitations](#other-known-limitations)
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+ - [Additional Information](#additional-information)
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+ - [Dataset Curators](#dataset-curators)
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+ - [Licensing Information](#licensing-information)
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+ - [Citation Information](#citation-information)
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+
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+ ## Dataset Description
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+
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+ - **Homepage:** [Homepage](https://github.com/AmrMehasseb/Emotional-Tone)
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+ - **Repository:** [Repository](https://github.com/AmrMehasseb/Emotional-Tone)
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+ - **Paper:** [Emotional Tone Detection in Arabic Tweets](https://www.researchgate.net/publication/328164296_Emotional_Tone_Detection_in_Arabic_Tweets_18th_International_Conference_CICLing_2017_Budapest_Hungary_April_17-23_2017_Revised_Selected_Papers_Part_II)
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+ - **Point of Contact:** [Amr Al-Khatib](https://github.com/AmrMehasseb)
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+
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+ ### Dataset Summary
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+
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+ Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text
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+
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+ ### Supported Tasks and Leaderboards
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+
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+ [More Information Needed]
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+
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+ ### Languages
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+
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+ The dataset is based on Arabic.
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+
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+ ## Dataset Structure
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+
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+ ### Data Instances
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+
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+ example:
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+ ```
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+ >>> {'label': 0, 'tweet': 'الاوليمبياد الجايه هكون لسه ف الكليه ..'}
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+ ```
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+
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+ ### Data Fields
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+
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+ - "tweet": plain text tweet in Arabic
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+
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+ - "label": emotion class label
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+
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+ the dataset distribution and balance for each class looks like the following
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+
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+ |label||Label description | Count |
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+ |---------|---------| ------- |
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+ |0 |none | 1550 |
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+ |1 |anger | 1444 |
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+ |2 |joy | 1281 |
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+ |3 |sadness | 1256 |
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+ |4 |love | 1220 |
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+ |5 |sympathy | 1062 |
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+ |6 |surprise | 1045 |
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+ |7 |fear | 1207 |
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+
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+ ### Data Splits
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+
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+ The dataset is not split.
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+
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+ | | Tain |
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+ |---------- | ------ |
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+ |no split | 10,065 |
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+
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+ ## Dataset Creation
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+
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+ ### Curation Rationale
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+
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+ [More Information Needed]
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+
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+ ### Source Data
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+
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+ [More Information Needed]
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+
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+ #### Initial Data Collection and Normalization
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+
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+ [More Information Needed]
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+
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+ #### Who are the source language producers?
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+
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+ [More Information Needed]
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+
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+ ### Annotations
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+
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+
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+
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+ #### Annotation process
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+
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+ [More Information Needed]
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+
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+ #### Who are the annotators?
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+
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+ [More Information Needed]
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+
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+ ### Personal and Sensitive Information
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+
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+ [More Information Needed]
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+
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+ ## Considerations for Using the Data
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+
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+ ### Discussion of Social Impact and Biases
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+
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+ [More Information Needed]
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+
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+ ### Other Known Limitations
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+
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+ [More Information Needed]
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+
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+ ## Additional Information
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+
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+ ### Dataset Curators
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+
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+ [More Information Needed]
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+
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+ ### Licensing Information
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+
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+ [More Information Needed]
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+
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+ ### Citation Information
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+
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+ @inbook{inbook,
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+ author = {Al-Khatib, Amr and El-Beltagy, Samhaa},
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+ year = {2018},
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+ month = {01},
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+ pages = {105-114},
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+ title = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II},
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+ isbn = {978-3-319-77115-1},
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+ doi = {10.1007/978-3-319-77116-8_8}
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+ }
dataset_infos.json ADDED
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+ {"default": {"description": "Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text", "citation": "@inbook{inbook,\nauthor = {Al-Khatib, Amr and El-Beltagy, Samhaa},\nyear = {2018},\nmonth = {01},\npages = {105-114},\ntitle = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17\u201323, 2017, Revised Selected Papers, Part II},\nisbn = {978-3-319-77115-1},\ndoi = {10.1007/978-3-319-77116-8_8}\n}\n", "homepage": "https://github.com/AmrMehasseb/Emotional-Tone", "license": "", "features": {"tweet": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 8, "names": ["none", "anger", "joy", "sadness", "love", "sympathy", "surprise", "fear"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "emotone_ar", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1541746, "num_examples": 10065, "dataset_name": "emotone_ar"}}, "download_checksums": {"https://raw.githubusercontent.com/AmrMehasseb/Emotional-Tone/master/Emotional-Tone-Dataset.csv": {"num_bytes": 1563138, "checksum": "f799c5ee86ea407de33609f1bbf607369fc7610551fa073b9fc59cd211098715"}}, "download_size": 1563138, "post_processing_size": null, "dataset_size": 1541746, "size_in_bytes": 3104884}}
dummy/0.0.0/dummy_data.zip ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:8d9d07709203c482fd89834c8b5df75def0e339a2727976af4a0ab2634dfd058
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+ size 551
emotone_ar.py ADDED
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+ # coding=utf-8
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+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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+ #
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+ # Licensed under the Apache License, Version 2.0 (the "License");
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+ # you may not use this file except in compliance with the License.
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+ # You may obtain a copy of the License at
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+ #
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+ # http://www.apache.org/licenses/LICENSE-2.0
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+ #
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+ # Unless required by applicable law or agreed to in writing, software
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+ # distributed under the License is distributed on an "AS IS" BASIS,
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+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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+ # See the License for the specific language governing permissions and
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+ # limitations under the License.
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+ """Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text """
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+
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+ from __future__ import absolute_import, division, print_function
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+
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+ import csv
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+
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+ import datasets
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+
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+
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+ _CITATION = """\
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+ @inbook{inbook,
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+ author = {Al-Khatib, Amr and El-Beltagy, Samhaa},
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+ year = {2018},
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+ month = {01},
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+ pages = {105-114},
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+ title = {Emotional Tone Detection in Arabic Tweets: 18th International Conference, CICLing 2017, Budapest, Hungary, April 17–23, 2017, Revised Selected Papers, Part II},
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+ isbn = {978-3-319-77115-1},
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+ doi = {10.1007/978-3-319-77116-8_8}
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+ }
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+ """
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+
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+
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+ _DESCRIPTION = """\
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+ Dataset of 10065 tweets in Arabic for Emotion detection in Arabic text"""
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+
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+
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+ _HOMEPAGE = "https://github.com/AmrMehasseb/Emotional-Tone"
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+
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+
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+ _DOWNLOAD_URL = "https://raw.githubusercontent.com/AmrMehasseb/Emotional-Tone/master/Emotional-Tone-Dataset.csv"
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+
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+
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+ class EmotoneAr(datasets.GeneratorBasedBuilder):
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+ """Dataset of 10065 tweets in Arabic for Emotions detection in Arabic text"""
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+
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+ def _info(self):
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+ return datasets.DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=datasets.Features(
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+ {
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+ "tweet": datasets.Value("string"),
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+ "label": datasets.features.ClassLabel(
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+ names=["none", "anger", "joy", "sadness", "love", "sympathy", "surprise", "fear"]
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+ ),
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+ }
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+ ),
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+ homepage=_HOMEPAGE,
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ """Returns SplitGenerators."""
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+ data_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)
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+ return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_dir})]
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+
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+ def _generate_examples(self, filepath):
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+ """Generate labeled arabic tweets examples for emoptions detection."""
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+ with open(filepath, encoding="utf-8", mode="r") as csv_file:
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+ next(csv_file) # skip header
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+ csv_reader = csv.reader(csv_file, quotechar='"', delimiter=",")
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+
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+ for id_, row in enumerate(csv_reader):
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+ _, tweet, label = row
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+ yield id_, {"tweet": tweet, "label": label}