system HF staff commited on
Commit
d5c7b9e
0 Parent(s):

Update files from the datasets library (from 1.2.0)

Browse files

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

.gitattributes ADDED
@@ -0,0 +1,27 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ *.7z filter=lfs diff=lfs merge=lfs -text
2
+ *.arrow filter=lfs diff=lfs merge=lfs -text
3
+ *.bin filter=lfs diff=lfs merge=lfs -text
4
+ *.bin.* filter=lfs diff=lfs merge=lfs -text
5
+ *.bz2 filter=lfs diff=lfs merge=lfs -text
6
+ *.ftz filter=lfs diff=lfs merge=lfs -text
7
+ *.gz filter=lfs diff=lfs merge=lfs -text
8
+ *.h5 filter=lfs diff=lfs merge=lfs -text
9
+ *.joblib filter=lfs diff=lfs merge=lfs -text
10
+ *.lfs.* filter=lfs diff=lfs merge=lfs -text
11
+ *.model filter=lfs diff=lfs merge=lfs -text
12
+ *.msgpack filter=lfs diff=lfs merge=lfs -text
13
+ *.onnx filter=lfs diff=lfs merge=lfs -text
14
+ *.ot filter=lfs diff=lfs merge=lfs -text
15
+ *.parquet filter=lfs diff=lfs merge=lfs -text
16
+ *.pb filter=lfs diff=lfs merge=lfs -text
17
+ *.pt filter=lfs diff=lfs merge=lfs -text
18
+ *.pth filter=lfs diff=lfs merge=lfs -text
19
+ *.rar filter=lfs diff=lfs merge=lfs -text
20
+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
21
+ *.tar.* filter=lfs diff=lfs merge=lfs -text
22
+ *.tflite filter=lfs diff=lfs merge=lfs -text
23
+ *.tgz filter=lfs diff=lfs merge=lfs -text
24
+ *.xz filter=lfs diff=lfs merge=lfs -text
25
+ *.zip filter=lfs diff=lfs merge=lfs -text
26
+ *.zstandard filter=lfs diff=lfs merge=lfs -text
27
+ *tfevents* filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,145 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ annotations_creators:
3
+ - crowdsourced
4
+ language_creators:
5
+ - found
6
+ languages:
7
+ - ja
8
+ licenses:
9
+ - cc-by-nd-4-0
10
+ multilinguality:
11
+ - monolingual
12
+ size_categories:
13
+ - 10K<n<100K
14
+ source_datasets:
15
+ - original
16
+ task_categories:
17
+ - text-classification
18
+ task_ids:
19
+ - fact-checking
20
+ ---
21
+
22
+ # Dataset Card for COVID-19 日本語Twitterデータセット (COVID-19 Japanese Twitter Dataset)
23
+
24
+ ## Table of Contents
25
+ - [Dataset Description](#dataset-description)
26
+ - [Dataset Summary](#dataset-summary)
27
+ - [Supported Tasks](#supported-tasks-and-leaderboards)
28
+ - [Languages](#languages)
29
+ - [Dataset Structure](#dataset-structure)
30
+ - [Data Instances](#data-instances)
31
+ - [Data Fields](#data-instances)
32
+ - [Data Splits](#data-instances)
33
+ - [Dataset Creation](#dataset-creation)
34
+ - [Curation Rationale](#curation-rationale)
35
+ - [Source Data](#source-data)
36
+ - [Annotations](#annotations)
37
+ - [Personal and Sensitive Information](#personal-and-sensitive-information)
38
+ - [Considerations for Using the Data](#considerations-for-using-the-data)
39
+ - [Social Impact of Dataset](#social-impact-of-dataset)
40
+ - [Discussion of Biases](#discussion-of-biases)
41
+ - [Other Known Limitations](#other-known-limitations)
42
+ - [Additional Information](#additional-information)
43
+ - [Dataset Curators](#dataset-curators)
44
+ - [Licensing Information](#licensing-information)
45
+ - [Citation Information](#citation-information)
46
+
47
+ ## Dataset Description
48
+
49
+ - **Homepage:** [COVID-19 日本語Twitterデータセット homepage](http://www.db.info.gifu-u.ac.jp/data/Data_5f02db873363f976fce930d1)
50
+ - **Repository:** [N/A]
51
+ - **Paper:** [N/A]
52
+ - **Leaderboard:** [N/A]
53
+ - **Point of Contact:** Check the homepage.
54
+
55
+ ### Dataset Summary
56
+
57
+ 53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. The annotation is by majority decision by 5 - 10 crowd workers. Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020. The original tweets are not contained. Please use Twitter API to get them, for example.
58
+
59
+ ### Supported Tasks and Leaderboards
60
+
61
+ Text-classification, Whether the tweet is related to COVID-19, and whether it is fact or opinion.
62
+
63
+ ### Languages
64
+
65
+ The text can be gotten using the IDs in this dataset is Japanese, posted on Twitter.
66
+
67
+ ## Dataset Structure
68
+
69
+ ### Data Instances
70
+
71
+ CSV file with the 1st column is Twitter ID and the 2nd column is assessment option ID.
72
+
73
+ ### Data Fields
74
+
75
+ - `tweet_id`: Twitter ID.
76
+ - `assessment_option_id`: The selection result. It has the following meanings:
77
+ - 63: a general fact: generally published information, such as news.
78
+ - 64: a personal fact: personal news. For example, a person heard that the next-door neighbor, XX, has infected COVID-19, which has not been in a news.
79
+ - 65: an opinion/feeling
80
+ - 66: difficult to determine if they are related to COVID-19 (it is definitely the tweet is not "67: unrelated", but 63, 64, 65 cannot be determined)
81
+ - 67: unrelated
82
+ - 68: it is a fact, but difficult to determine whether general facts, personal facts, or impressions (it may be irrelevant to COVID-19 since it is indistinguishable between 63 - 65 and 67).
83
+
84
+ ### Data Splits
85
+
86
+ [More Information Needed]
87
+
88
+ ## Dataset Creation
89
+
90
+ ### Curation Rationale
91
+
92
+ [More Information Needed] because the paper is not yet published.
93
+
94
+ ### Source Data
95
+
96
+ #### Initial Data Collection and Normalization
97
+
98
+ 53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020.
99
+
100
+ #### Who are the source language producers?
101
+
102
+ The language producers are users of Twitter.
103
+
104
+ ### Annotations
105
+
106
+ #### Annotation process
107
+
108
+ The annotation is by majority decision by 5 - 10 crowd workers.
109
+
110
+ #### Who are the annotators?
111
+
112
+ Crowd workers.
113
+
114
+ ### Personal and Sensitive Information
115
+
116
+ The author does not contain original tweets.
117
+
118
+ ## Considerations for Using the Data
119
+
120
+ ### Social Impact of Dataset
121
+
122
+ [More Information Needed]
123
+
124
+ ### Discussion of Biases
125
+
126
+ [More Information Needed]
127
+
128
+ ### Other Known Limitations
129
+
130
+ [More Information Needed]
131
+
132
+ ## Additional Information
133
+
134
+ ### Dataset Curators
135
+
136
+ The dataset is hosted by Suzuki Laboratory, Gifu University, Japan.
137
+
138
+ ### Licensing Information
139
+
140
+ CC-BY-ND 4.0
141
+
142
+ ### Citation Information
143
+
144
+ A related paper has not yet published.
145
+ The author shows how to cite as「鈴木 優: COVID-19 日本語 Twitter データセット(http://www.db.info.gifu-u.ac.jp/data/Data_5f02db873363f976fce930d1)」.
covid_tweets_japanese.py ADDED
@@ -0,0 +1,92 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # coding=utf-8
2
+ # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
3
+ #
4
+ # Licensed under the Apache License, Version 2.0 (the "License");
5
+ # you may not use this file except in compliance with the License.
6
+ # You may obtain a copy of the License at
7
+ #
8
+ # http://www.apache.org/licenses/LICENSE-2.0
9
+ #
10
+ # Unless required by applicable law or agreed to in writing, software
11
+ # distributed under the License is distributed on an "AS IS" BASIS,
12
+ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13
+ # See the License for the specific language governing permissions and
14
+ # limitations under the License.
15
+ """COVID-19 Japanese Tweets Dataset."""
16
+
17
+ from __future__ import absolute_import, division, print_function
18
+
19
+ import bz2
20
+ import csv
21
+
22
+ import datasets
23
+
24
+
25
+ _CITATION = """\
26
+ No paper about this dataset is published yet. \
27
+ Please cite this dataset as "鈴木 優: COVID-19 日本語 Twitter データセット (http://www.db.info.gifu-u.ac.jp/data/Data_5f02db873363f976fce930d1)"
28
+ """
29
+
30
+ _DESCRIPTION = """\
31
+ 53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. The annotation is by majority decision by 5 - 10 crowd workers. \
32
+ Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020. \
33
+ The original tweets are not contained. Please use Twitter API to get them, for example.
34
+ """
35
+
36
+ _HOMEPAGE = "http://www.db.info.gifu-u.ac.jp/data/Data_5f02db873363f976fce930d1"
37
+
38
+ _LICENSE = "CC-BY-ND 4.0"
39
+
40
+ # The HuggingFace dataset library don't host the datasets but only point to the original files
41
+ # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
42
+ _URLs = {
43
+ "url": "http://www.db.info.gifu-u.ac.jp/data/data.csv.bz2",
44
+ }
45
+
46
+
47
+ class CovidTweetsJapanese(datasets.GeneratorBasedBuilder):
48
+ """COVID-19 Japanese Tweets Dataset."""
49
+
50
+ VERSION = datasets.Version("1.1.0")
51
+
52
+ def _info(self):
53
+ features = datasets.Features(
54
+ {
55
+ "tweet_id": datasets.Value("string"),
56
+ "assessment_option_id": datasets.ClassLabel(names=["63", "64", "65", "66", "67", "68"]),
57
+ }
58
+ )
59
+ return datasets.DatasetInfo(
60
+ description=_DESCRIPTION,
61
+ features=features,
62
+ supervised_keys=None,
63
+ homepage=_HOMEPAGE,
64
+ license=_LICENSE,
65
+ citation=_CITATION,
66
+ )
67
+
68
+ def _split_generators(self, dl_manager):
69
+ """Returns SplitGenerators."""
70
+
71
+ my_urls = _URLs["url"]
72
+ # data_url = dl_manager.download_and_extract(my_urls)
73
+ data_url = dl_manager.download(my_urls)
74
+
75
+ return [
76
+ datasets.SplitGenerator(
77
+ name=datasets.Split.TRAIN,
78
+ gen_kwargs={"filepath": data_url, "split": "train"},
79
+ ),
80
+ ]
81
+
82
+ def _generate_examples(self, filepath, split):
83
+ """ Yields examples. """
84
+
85
+ with bz2.open(filepath, "rt") as f:
86
+ data = csv.reader(f)
87
+ _ = next(data)
88
+ for id_, row in enumerate(data):
89
+ yield id_, {
90
+ "tweet_id": row[0],
91
+ "assessment_option_id": row[1],
92
+ }
dataset_infos.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"default": {"description": "53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. The annotation is by majority decision by 5 - 10 crowd workers. Target tweets include \"COVID\" or \"\u30b3\u30ed\u30ca\". The period of the tweets is from around January 2020 to around June 2020. The original tweets are not contained. Please use Twitter API to get them, for example.\n", "citation": "No paper about this dataset is published yet. Please cite this dataset as \"\u9234\u6728 \u512a: COVID-19 \u65e5\u672c\u8a9e Twitter \u30c7\u30fc\u30bf\u30bb\u30c3\u30c8 \uff08http://www.db.info.gifu-u.ac.jp/data/Data_5f02db873363f976fce930d1\uff09\"\n", "homepage": "http://www.db.info.gifu-u.ac.jp/data/Data_5f02db873363f976fce930d1", "license": "CC-BY-ND 4.0", "features": {"tweet_id": {"dtype": "string", "id": null, "_type": "Value"}, "assessment_option_id": {"num_classes": 6, "names": ["63", "64", "65", "66", "67", "68"], "names_file": null, "id": null, "_type": "ClassLabel"}}, "post_processed": null, "supervised_keys": null, "builder_name": "covid_tweets_japanese", "config_name": "default", "version": {"version_str": "1.1.0", "description": null, "major": 1, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1662833, "num_examples": 53639, "dataset_name": "covid_tweets_japanese"}}, "download_checksums": {"http://www.db.info.gifu-u.ac.jp/data/data.csv.bz2": {"num_bytes": 406005, "checksum": "b1023e49df7717db7eedf3b318511b6163ec2651cbf78a8d72f7e1e0bc3fd4c6"}}, "download_size": 406005, "post_processing_size": null, "dataset_size": 1662833, "size_in_bytes": 2068838}}
dummy/1.1.0/dummy_data.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6374a010e20a5e8994f5b5c51dab1e9f3f2b536255cc66ffca407247db20b40e
3
+ size 472