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spamid_pair.py

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+# coding=utf-8
+# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+import pandas as pd
+
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import Licenses, Tasks
+
+_CITATION = """\
+@article{Chrismanto2022,
+title = {SPAMID-PAIR: A Novel Indonesian Post–Comment Pairs Dataset Containing Emoji},
+journal = {International Journal of Advanced Computer Science and Applications},
+doi = {10.14569/IJACSA.2022.0131110},
+url = {http://dx.doi.org/10.14569/IJACSA.2022.0131110},
+year = {2022},
+publisher = {The Science and Information Organization},
+volume = {13},
+number = {11},
+author = {Antonius Rachmat Chrismanto and Anny Kartika Sari and Yohanes Suyanto}
+}
+"""
+
+_DATASETNAME = "spamid_pair"
+
+
+_DESCRIPTION = """\
+SPAMID-PAIR is data post-comment pairs collected from 13 selected Indonesian public figures (artists) / public accounts
+with more than 15 million followers and categorized as famous artists.
+It was collected from Instagram using an online tool and Selenium.
+Two persons labeled all pair data as an expert in a total of 72874 data.
+The data contains Unicode text (UTF-8) and emojis scrapped in posts and comments without account profile information.
+"""
+
+_HOMEPAGE = "https://data.mendeley.com/datasets/fj5pbdf95t/1"
+
+_LANGUAGES = ["ind"]
+
+
+_LICENSE = Licenses.CC_BY_4_0.value
+
+_LOCAL = False
+
+
+_URLS = {
+    _DATASETNAME: "https://prod-dcd-datasets-cache-zipfiles.s3.eu-west-1.amazonaws.com/fj5pbdf95t-1.zip",
+}
+
+_SUPPORTED_TASKS = [Tasks.INTENT_CLASSIFICATION]
+
+_SOURCE_VERSION = "1.0.0"
+
+_SEACROWD_VERSION = "2024.06.20"
+
+
+class SpamidPairDataset(datasets.GeneratorBasedBuilder):
+    """SPAMID-PAIR is data post-comment pairs collected from 13 selected Indonesian public figures (artists) / public accounts with more than 15 million followers and categorized as famous artists."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
+
+    LABEL_CLASSES = [1, 0]
+
+    SEACROWD_SCHEMA_NAME = "text"
+
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_source",
+            version=SOURCE_VERSION,
+            description=f"{_DATASETNAME} source schema",
+            schema="source",
+            subset_id=_DATASETNAME,
+        ),
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_seacrowd_{SEACROWD_SCHEMA_NAME}",
+            version=SEACROWD_VERSION,
+            description=f"{_DATASETNAME} SEACrowd schema",
+            schema=f"seacrowd_{SEACROWD_SCHEMA_NAME}",
+            subset_id=_DATASETNAME,
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "igid": datasets.Value("string"),
+                    "comment": datasets.Value("string"),
+                    "posting": datasets.Value("string"),
+                    "spam": datasets.ClassLabel(names=self.LABEL_CLASSES),
+                }
+            )
+
+        elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}":
+            features = schemas.text_features(self.LABEL_CLASSES)
+
+        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."""
+        urls = _URLS[_DATASETNAME]
+        data_dir = Path(dl_manager.download_and_extract(urls))
+        data_dir = os.path.join(os.path.join(os.path.join(data_dir, "SPAMID-PAIR"), "Raw"), "dataset-raw.xlsx")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir,
+                    "split": "train",
+                },
+            )
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        data = pd.read_excel(filepath)
+
+        if self.config.schema == "source":
+            for i, row in data.iterrows():
+                yield i, {
+                    "igid": str(row["igid"]),
+                    "comment": str(row["comment"]),
+                    "posting": str(row["posting"]),
+                    "spam": row["spam"],
+                }
+
+        elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}":
+            for i, row in data.iterrows():
+                yield i, {
+                    "id": str(i),
+                    "text": str(row["comment"]) + "\n" + str(row["posting"]),
+                    "label": int(row["spam"]),
+                }