Host data files and update dates (#1)

- Add data file (0f26a0cc23ea8aa19afcb11a79b0eba4630a2f42)
- Update loading script (f18514cd1fd20dbda5b98f28a5304fb452709064)
- Update metadata num_examples from 1090591 to 2541575 (f0059d7d03589a431143b09336c3f8210680ccd5)
- Update script to iterate data files for all dates (5b609e65a8b2842d4f0b8dbab2c70585fde7cf6d)
- Update metadata num_examples from 2541575 to 3140158 (86fb2fd673767d9dbcc967010320ea1453928272)
- Update metadata dates in dataset card (09034ad1097e28c418049ff188807a75978cc6d1)
- Delete legacy dataset_infos.json (4b119b723b16ee8bb7b020a558d3c7513f68c07e)

README.md

@@ -19,16 +19,16 @@ pretty_name: ArCOV19
 tags:
 - data-mining
 dataset_info:
+  config_name: ar_cov19
   features:
   - name: tweetID
     dtype: int64
-  config_name: ar_cov19
   splits:
   - name: train
-    num_bytes: 8724728
-    num_examples: 1090591
-  download_size: 54902390
-  dataset_size: 8724728
+    num_bytes: 25121264
+    num_examples: 3140158
+  download_size: 23678407
+  dataset_size: 25121264
 ---
 
 # Dataset Card for ArCOV19
@@ -67,7 +67,15 @@ dataset_info:
 
 ### Dataset Summary
 
-ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is the first publicly-available Arabic Twitter dataset covering COVID-19 pandemic that includes over 1M tweets alongside the propagation networks of the most-popular subset of them (i.e., most-retweeted and-liked). The propagation networks include both retweets and conversational threads (i.e., threads of replies). ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others. Preliminary analysis shows that ArCOV-19 captures rising discussions associated with the first reported cases of the disease as they appeared in the Arab world. In addition to the source tweets and the propagation networks, we also release the search queries and the language-independent crawler used to collect the tweets to encourage the curation of similar datasets.
+ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 5th of May 2021.
+ArCOV-19 is the first publicly-available Arabic Twitter dataset covering COVID-19 pandemic that includes about 3.2M
+tweets alongside the propagation networks of the most-popular subset of them (i.e., most-retweeted and-liked).
+The propagation networks include both retweets and conversational threads (i.e., threads of replies).
+ArCOV-19 is designed to enable research under several domains including natural language processing, information
+retrieval, and social computing, among others. Preliminary analysis shows that ArCOV-19 captures rising discussions
+associated with the first reported cases of the disease as they appeared in the Arab world. In addition to the source
+tweets and the propagation networks, we also release the search queries and the language-independent crawler used to
+collect the tweets to encourage the curation of similar datasets.
 
 ### Supported Tasks and Leaderboards
 
@@ -155,12 +163,16 @@ No annotation was provided with the dataset.
 
 ### Citation Information
 
+```
 @article{haouari2020arcov19,
-  title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},
-  author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},
-  journal={arXiv preprint arXiv:2004.05861},
-  year={2020}
+      title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},
+      author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},
+      year={2021},
+      eprint={2004.05861},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
 }
+```
 
 ### Contributions
 

ar_cov19.py

@@ -48,7 +48,7 @@ _HOMEPAGE = "https://gitlab.com/bigirqu/ArCOV-19"
 # TODO: Add link to the official dataset URLs here
 # The HuggingFace dataset library don't host the datasets but only point to the original files
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_URL = "https://gitlab.com/bigirqu/ArCOV-19/-/archive/master/ArCOV-19-master.zip"
+_URL = "dataset-all_tweets.zip"
 # _URL="https://gitlab.com/bigirqu/ArCOV-19/-/archive/master/ArCOV-19-master.zip?path=dataset/all_tweets"
 
 
@@ -121,14 +121,15 @@ class ArCov19(datasets.GeneratorBasedBuilder):
         # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
         # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
         data_dir = dl_manager.download_and_extract(_URL)
-        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"data_dir": data_dir})]
+        data_files = dl_manager.iter_files(data_dir)
+        return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"data_files": data_files})]
 
-    def _generate_examples(self, data_dir):
+    def _generate_examples(self, data_files):
         """Yields examples."""
         # TODO: This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method.
         # It is in charge of opening the given file and yielding (key, example) tuples from the dataset
         # The key is not important, it's more here for legacy reason (legacy from tfds)
-        for fname in sorted(glob.glob(os.path.join(data_dir, "ArCOV-19-master/dataset/all_tweets/2020-*"))):
+        for fname in data_files:
 
             df = pd.read_csv(fname, names=["tweetID"])
             for id_, record in df.iterrows():

dataset-all_tweets.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2c503fcf94f768847e59323aca91052bf22c3f102a01ece358ea421cf3abcbde
+size 23678407

dataset_infos.json

@@ -1 +0,0 @@
-{"ar_cov19": {"description": "ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others\n", "citation": "@article{haouari2020arcov19,\n  title={ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks},\n  author={Fatima Haouari and Maram Hasanain and Reem Suwaileh and Tamer Elsayed},\n  journal={arXiv preprint arXiv:2004.05861},\n  year={2020}\n", "homepage": "https://gitlab.com/bigirqu/ArCOV-19", "license": "", "features": {"tweetID": {"dtype": "int64", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "ar_cov19", "config_name": "ar_cov19", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 8724728, "num_examples": 1090591, "dataset_name": "ar_cov19"}}, "download_checksums": {"https://gitlab.com/bigirqu/ArCOV-19/-/archive/master/ArCOV-19-master.zip": {"num_bytes": 54902390, "checksum": "96211408035f8082c072a5eb4fbccf28ef4de00379abfc9523c552ab84646579"}}, "download_size": 54902390, "post_processing_size": null, "dataset_size": 8724728, "size_in_bytes": 63627118}}