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id_hatespeech.py

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+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+import pandas as pd
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+
+_CITATION = """\
+@inproceedings{inproceedings,
+author = {Alfina, Ika and Mulia, Rio and Fanany, Mohamad Ivan and Ekanata, Yudo},
+year = {2017},
+month = {10},
+pages = {},
+title = {Hate Speech Detection in the Indonesian Language: A Dataset and Preliminary Study},
+doi = {10.1109/ICACSIS.2017.8355039}
+}
+"""
+
+_LOCAL = False
+_LANGUAGES = ["ind"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_DATASETNAME = "id_hatespeech"
+
+_DESCRIPTION = """\
+The ID Hatespeech dataset is collection of 713 tweets related to a political event, the Jakarta Governor Election 2017
+designed for hate speech detection NLP task. This dataset is crawled from Twitter, and then filtered
+and annotated manually. The dataset labelled into two; HS if the tweet contains hate speech and Non_HS if otherwise
+"""
+
+_HOMEPAGE = "https://www.researchgate.net/publication/320131169_Hate_Speech_Detection_in_the_Indonesian_Language_A_Dataset_and_Preliminary_Study"
+_LICENSE = "Unknown"
+_URLS = {
+    _DATASETNAME: "https://raw.githubusercontent.com/ialfina/id-hatespeech-detection/master/IDHSD_RIO_unbalanced_713_2017.txt",
+}
+_SUPPORTED_TASKS = [Tasks.SENTIMENT_ANALYSIS]
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class IdHatespeech(datasets.GeneratorBasedBuilder):
+    """The ID Hatespeech dataset is collection of tweets related to a political event, the Jakarta Governor Election 2017
+    designed for hate speech detection NLP task."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="id_hatespeech_source",
+            version=SOURCE_VERSION,
+            description="ID Hatespeech source schema",
+            schema="source",
+            subset_id="id_hatespeech",
+        ),
+        NusantaraConfig(
+            name="id_hatespeech_nusantara_text",
+            version=NUSANTARA_VERSION,
+            description="ID Hatespeech Nusantara schema",
+            schema="nusantara_text",
+            subset_id="id_hatespeech",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "id_hatespeech_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features({"tweet": datasets.Value("string"), "label": datasets.Value("string")})
+        elif self.config.schema == "nusantara_text":
+            features = schemas.text_features(["Non_HS", "HS"])
+   
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        """Returns SplitGenerators."""
+        # Dataset does not have predetermined split, putting all as TRAIN
+        urls = _URLS[_DATASETNAME]
+        base_dir = Path(dl_manager.download_and_extract(urls))
+        data_files = {"train": base_dir}
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_files["train"],
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        # Dataset does not have id, using row index as id
+        df = pd.read_csv(filepath, sep="\t", encoding="ISO-8859-1").reset_index()
+        df.columns = ["id", "label", "tweet"]
+
+        if self.config.schema == "source":
+            for row in df.itertuples():
+                ex = {
+                    "tweet": row.tweet,
+                    "label": row.label,
+                }
+                yield row.id, ex
+
+        elif self.config.schema == "nusantara_text":
+            for row in df.itertuples():
+                ex = {
+                    "id": str(row.id),
+                    "text": row.tweet,
+                    "label": row.label,
+                }
+                yield row.id, ex
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")