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karonese_sentiment.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 = """\
+@article{karo2022sentiment,
+  title={Sentiment Analysis in Karonese Tweet using Machine Learning},
+  author={Karo, Ichwanul Muslim Karo and Fudzee, Mohd Farhan Md and Kasim, Shahreen and Ramli, Azizul Azhar},
+  journal={Indonesian Journal of Electrical Engineering and Informatics (IJEEI)},
+  volume={10},
+  number={1},
+  pages={219--231},
+  year={2022}
+}
+"""
+
+_LANGUAGES = ["btx"]
+_LOCAL = False
+
+_DATASETNAME = "karonese_sentiment"
+
+_DESCRIPTION = """\
+Karonese sentiment was crawled from Twitter between 1 January 2021 and 31 October 2021.
+The first crawling process used several keywords related to the Karonese, such as
+"deleng sinabung, Sinabung mountain", "mejuah-juah, greeting welcome", "Gundaling",
+and so on. However, due to the insufficient number of tweets obtained using such
+keywords, a second crawling process was done based on several hashtags, such as
+#kalakkaro, # #antonyginting, and #lyodra.
+"""
+
+_HOMEPAGE = "http://section.iaesonline.com/index.php/IJEEI/article/view/3565"
+
+_LICENSE = "Unknown"
+
+_URLS = {
+    _DATASETNAME: "https://raw.githubusercontent.com/aliakbars/karonese/main/karonese_sentiment.csv",
+}
+
+_SUPPORTED_TASKS = [Tasks.SENTIMENT_ANALYSIS]
+
+_SOURCE_VERSION = "1.0.0"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class KaroneseSentimentDataset(datasets.GeneratorBasedBuilder):
+    """Karonese sentiment was crawled from Twitter between 1 January 2021 and 31 October 2021.
+    The dataset consists of 397 negative, 342 neutral, and 260 positive tweets.
+    """
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="karonese_sentiment_source",
+            version=SOURCE_VERSION,
+            description="Karonese Sentiment source schema",
+            schema="source",
+            subset_id="karonese_sentiment",
+        ),
+        NusantaraConfig(
+            name="karonese_sentiment_nusantara_text",
+            version=NUSANTARA_VERSION,
+            description="Karonese Sentiment Nusantara schema",
+            schema="nusantara_text",
+            subset_id="karonese_sentiment",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "sentiment_nathasa_review_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "no": datasets.Value("string"),
+                    "tweet": datasets.Value("string"),
+                    "label": datasets.Value("string"),
+                }
+            )
+        elif self.config.schema == "nusantara_text":
+            features = schemas.text_features(["negative", "neutral", "positive"])
+
+        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
+        data_dir = Path(dl_manager.download_and_extract(_URLS[_DATASETNAME]))
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        df = pd.read_csv(filepath).drop("no", axis=1)
+        df.columns = ["text", "label"]
+
+        if self.config.schema == "source":
+            for idx, row in df.iterrows():
+                example = {
+                    "no": str(idx+1),
+                    "tweet": row.text,
+                    "label": row.label,
+                }
+                yield idx, example
+        elif self.config.schema == "nusantara_text":
+            for idx, row in df.iterrows():
+                example = {
+                    "id": str(idx+1),
+                    "text": row.text,
+                    "label": row.label,
+                }
+                yield idx, example
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")