Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
Tags:
License:
albertvillanova HF staff commited on
Commit
083b117
1 Parent(s): 8943dd1

Update loading script with local data file

Browse files
Files changed (1) hide show
  1. hate_speech18.py +10 -24
hate_speech18.py CHANGED
@@ -47,7 +47,7 @@ forums posts have been sampled from several subforums and split into sentences.
47
  have been manually labelled as containing hate speech or not, according to certain annotation guidelines.
48
  """
49
 
50
- _DATA_URL = "https://github.com/Vicomtech/hate-speech-dataset/archive/master.zip"
51
 
52
 
53
  class HateSpeech18(datasets.GeneratorBasedBuilder):
@@ -75,35 +75,21 @@ class HateSpeech18(datasets.GeneratorBasedBuilder):
75
 
76
  return [
77
  datasets.SplitGenerator(
78
- name=datasets.Split.TRAIN, gen_kwargs={"filepath": os.path.join(dl_dir, "hate-speech-dataset-master")}
79
  ),
80
  ]
81
 
82
- def _generate_examples(self, filepath):
83
-
84
- with open(os.path.join(filepath, "annotations_metadata.csv"), encoding="utf-8") as csv_file:
85
-
86
- csv_reader = csv.reader(
87
  csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
88
  )
89
-
90
- next(csv_reader)
91
-
92
  for idx, row in enumerate(csv_reader):
93
-
94
- file_id, user_id, subforum_id, num_contexts, label = row
95
-
96
- all_files_path = os.path.join(filepath, "all_files")
97
-
98
- path = os.path.join(all_files_path, file_id + ".txt")
99
-
100
- with open(path, encoding="utf-8") as file:
101
- text = file.read()
102
-
103
  yield idx, {
104
  "text": text,
105
- "user_id": user_id,
106
- "subforum_id": subforum_id,
107
- "num_contexts": num_contexts,
108
- "label": label,
109
  }
 
47
  have been manually labelled as containing hate speech or not, according to certain annotation guidelines.
48
  """
49
 
50
+ _DATA_URL = "data.zip"
51
 
52
 
53
  class HateSpeech18(datasets.GeneratorBasedBuilder):
 
75
 
76
  return [
77
  datasets.SplitGenerator(
78
+ name=datasets.Split.TRAIN, gen_kwargs={"data_dir": os.path.join(dl_dir, "data")}
79
  ),
80
  ]
81
 
82
+ def _generate_examples(self, data_dir):
83
+ all_files_path = os.path.join(data_dir, "all_files")
84
+ with open(os.path.join(data_dir, "annotations_metadata.csv"), encoding="utf-8") as csv_file:
85
+ csv_reader = csv.DictReader(
 
86
  csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
87
  )
 
 
 
88
  for idx, row in enumerate(csv_reader):
89
+ text_path = os.path.join(all_files_path, row.pop("file_id") + ".txt")
90
+ with open(text_path, encoding="utf-8") as text_file:
91
+ text = text_file.read()
 
 
 
 
 
 
 
92
  yield idx, {
93
  "text": text,
94
+ **row,
 
 
 
95
  }