Upload SOCKET.py

SOCKET.py

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+# coding=utf-8
+# Copyright 2020 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.
+"""The SOCKET Datasets"""
+
+
+import datasets
+
+
+_CITATION = """
+@misc{choi2023llms,
+      title={Do LLMs Understand Social Knowledge? Evaluating the Sociability of Large Language Models with SocKET Benchmark}, 
+      author={Minje Choi and Jiaxin Pei and Sagar Kumar and Chang Shu and David Jurgens},
+      year={2023},
+      eprint={2305.14938},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+A unified evaluation benchmark dataset for evaludating socialbility of NLP models.
+"""
+
+_HOMEPAGE = "TBD"
+
+_LICENSE = ""
+
+#set up url or the file dir here
+URL = "SOCKET_DATA/"
+URL = "https://huggingface.co/datasets/Blablablab/SOCKET/tree/main/SOCKET_DATA/"
+
+TASK_DICT = {
+    'humor_sarcasm': [
+        'hahackathon#humor_rating',
+        'humor-pairs',
+        'sarc',
+        'tweet_irony',
+        'hahackathon#is_humor',
+    ],
+    'offensive': [
+        'contextual-abuse#IdentityDirectedAbuse',
+        'contextual-abuse#PersonDirectedAbuse',
+        'hahackathon#offense_rating',
+        'hasbiasedimplication',
+        'hateoffensive',
+        'implicit-hate#explicit_hate',
+        'implicit-hate#implicit_hate',
+        'implicit-hate#incitement_hate',
+        'implicit-hate#inferiority_hate',
+        'implicit-hate#stereotypical_hate',
+        'implicit-hate#threatening_hate',
+        'implicit-hate#white_grievance_hate',
+        'intentyn',
+        'jigsaw#severe_toxic',
+        'jigsaw#identity_hate',
+        'jigsaw#threat',
+        'jigsaw#obscene',
+        'jigsaw#insult',
+        'jigsaw#toxic',
+        'offensiveyn',
+        'sexyn',
+        'talkdown-pairs',
+        'toxic-span',
+        'tweet_offensive'
+    ],
+    'sentiment_emotion': [
+        'crowdflower',
+        'dailydialog',
+        'emobank#arousal',
+        'emobank#dominance',
+        'emobank#valence',
+        'emotion-span',
+        'empathy#distress',
+        'empathy#distress_bin',
+        'same-side-pairs',
+        'sentitreebank',
+        'tweet_emoji',
+        'tweet_emotion',
+        'tweet_sentiment'
+    ],
+    'social_factors': [
+        'complaints',
+        'empathy#empathy',
+        'empathy#empathy_bin',
+        'hayati_politeness',
+        'questionintimacy',
+        'stanfordpoliteness'
+    ],
+    'trustworthy': [
+        'bragging#brag_achievement',
+        'bragging#brag_action',
+        'bragging#brag_possession',
+        'bragging#brag_trait',
+        'hypo-l',
+        'neutralizing-bias-pairs',
+        'propaganda-span',
+        'rumor#rumor_bool',
+        'two-to-lie#receiver_truth',
+        'two-to-lie#sender_truth',
+    ]
+}
+
+task2category = {}
+for category, tasks in TASK_DICT.items():
+    for task in tasks:
+        task2category[task] = category
+
+TASK_NAMES = []
+for tasks in TASK_DICT.values():
+    TASK_NAMES.extend(tasks)
+TASK_NAMES = sorted(TASK_NAMES)
+
+print(len(TASK_NAMES))
+_URLs = {}
+for task in TASK_NAMES:
+    _URLs[task] = {}
+    for s in ['train', 'test', 'val']:
+        for t in ['text', 'labels']:
+            task_url = '%s%s/%s_%s.txt'%(URL,task,s,t)
+            task_url = task_url.replace('#','%23')
+            _URLs[task][s + '_' + t] = task_url
+
+class SOCKETConfig(datasets.BuilderConfig):
+    def __init__(self, *args, type=None, sub_type=None, **kwargs):
+        super().__init__(
+            *args,
+            name=f"{type}",
+            **kwargs,
+        )
+        self.type = type
+        self.sub_type = sub_type
+
+
+class SOCKET(datasets.GeneratorBasedBuilder):
+    """SOCKET Dataset."""
+
+    BUILDER_CONFIGS = [
+        SOCKETConfig(
+            type=key,
+            sub_type=None,
+            version=datasets.Version("1.1.0"),
+            description=f"This part of my dataset covers {key} part of SocialEval Dataset.",
+        )
+        for key in list(TASK_NAMES)
+    ] 
+
+    def _info(self):
+        if self.config.type == "questionintimacy": 
+            names = ['Very-intimate', 'Intimate', 'Somewhat-intimate', 'Not-very-intimate', 'Not-intimate', 'Not-intimate-at-all']
+        elif self.config.type == "sexyn": 
+            names = ['not sexism', 'sexism']
+        elif self.config.type == "intentyn": 
+            names = ['not intentional', 'intentional']
+        elif self.config.type == "offensiveyn": 
+            names = ['not offensive', 'offensive']
+        elif self.config.type == "hasbiasedimplication": 
+            names = ['not biased', 'biased']
+        elif self.config.type == "trofi": 
+            names = ['metaphor', 'non-metaphor']
+        elif self.config.type == "sentitreebank": 
+            names = ['positive', 'negative']
+        elif self.config.type == "sarc": 
+            names = ['sarcastic', 'literal']
+        elif self.config.type == "stanfordpoliteness": 
+            names = ['polite', 'impolite']
+        elif self.config.type == "sarcasmghosh": 
+            names = ['sarcastic', 'literal']
+        elif self.config.type == "dailydialog": 
+            names = ['noemotion', 'anger', 'disgust', 'fear', 'happiness', 'sadness', 'surprise']
+        elif self.config.type == "shortromance": 
+            names = ['romantic', 'literal']
+        elif self.config.type == "crowdflower": 
+            names = ['empty', 'sadness', 'enthusiasm', 'neutral', 'worry', 'love', 'fun', 'hate', 'happiness', 'relief', 'boredom', 'surprise', 'anger']
+        elif self.config.type == "vua": 
+            names = ['metaphor', 'non-metaphor']
+        elif self.config.type == "shorthumor": 
+            names = ['humorous', 'literal']
+        elif self.config.type == "shortjokekaggle": 
+            names = ['humorous', 'literal']
+        elif self.config.type == "hateoffensive": 
+            names = ['hate', 'offensive', 'neither']
+        elif self.config.type == "emobank#valence": 
+            names = ['valence(positive)']
+        elif self.config.type == "emobank#arousal": 
+            names = ['arousal(excited)']
+        elif self.config.type == "emobank#dominance": 
+            names = ['dominance(being_in_control)']
+        elif self.config.type == "hayati_politeness": 
+            names = ['impolite', 'polite']
+        elif self.config.type == "jigsaw#toxic": 
+            names = ['not toxic', 'toxic']
+        elif self.config.type == "jigsaw#severe_toxic": 
+            names = ['not severe toxic', 'severe toxic']
+        elif self.config.type == "jigsaw#obscene": 
+            names = ['not obscene', 'obscene']
+        elif self.config.type == "jigsaw#threat": 
+            names = ['not threat', 'threat']
+        elif self.config.type == "jigsaw#insult": 
+            names = ['not insult', 'insult']
+        elif self.config.type == "jigsaw#identity_hate": 
+            names = ['not identity hate', 'identity hate']
+        elif self.config.type == "standup-comedy": 
+            names = ['not funny', 'funny']
+        elif self.config.type == "complaints": 
+            names = ['not complaint', 'complaint']
+        elif self.config.type == "hypo-l": 
+            names = ['not hyperbole', 'hyperbole']
+        elif self.config.type == "bragging#brag_action": 
+            names = ['not action bragging', 'action bragging']
+        elif self.config.type == "bragging#brag_feeling": 
+            names = ['not feeling bragging', 'feeling bragging']
+        elif self.config.type == "bragging#brag_achievement": 
+            names = ['not achievement bragging', 'achievement bragging']
+        elif self.config.type == "bragging#brag_possession": 
+            names = ['not possession bragging', 'possession bragging']
+        elif self.config.type == "bragging#brag_trait": 
+            names = ['not trait bragging', 'trait bragging']
+        elif self.config.type == "bragging#brag_affiliation": 
+            names = ['not affiliation bragging', 'affiliation bragging']
+        elif self.config.type == "contextual-abuse#IdentityDirectedAbuse": 
+            names = ['not identity directed abuse', 'identity directed abuse']
+        elif self.config.type == "contextual-abuse#AffiliationDirectedAbuse": 
+            names = ['not affiliation directed abuse', 'affiliation directed abuse']
+        elif self.config.type == "contextual-abuse#PersonDirectedAbuse": 
+            names = ['not person directed abuse', 'person directed abuse']
+        elif self.config.type == "contextual-abuse#CounterSpeech": 
+            names = ['not counter speech', 'counter speech']
+        elif self.config.type == "hahackathon#is_humor": 
+            names = ['not humor', 'humor']
+        elif self.config.type == "hahackathon#humor_rating": 
+            names = ['humor rating']
+        elif self.config.type == "hahackathon#offense_rating": 
+            names = ['offense rating']
+        elif self.config.type == "check_worthiness": 
+            names = ['not check-worthy', 'check-worthy']
+        elif self.config.type == "rumor#rumor_tf": 
+            names = ['not rumor tf', 'rumor tf']
+        elif self.config.type == "rumor#rumor_bool": 
+            names = ['not rumor', 'rumor']
+        elif self.config.type == "two-to-lie#deception": 
+            names = ['not deception', 'deception']
+        elif self.config.type == "two-to-lie#sender_truth": 
+            names = ['lie', 'truth']
+        elif self.config.type == "two-to-lie#receiver_truth": 
+            names = ['lie', 'truth']
+        elif self.config.type == "deceitful-reviews#true_rumor": 
+            names = ['fake review', 'true review']
+        elif self.config.type == "deceitful-reviews#positive": 
+            names = ['negative', 'positive']
+        elif self.config.type == "empathy#empathy": 
+            names = ['empathy']
+        elif self.config.type == "empathy#distress": 
+            names = ['distress']
+        elif self.config.type == "empathy#empathy_bin": 
+            names = ['not empathy', 'empathy']
+        elif self.config.type == "empathy#distress_bin": 
+            names = ['not distress', 'distress bin']
+        elif self.config.type == "implicit-hate#explicit_hate": 
+            names = ['not explicit hate', 'explicit hate']
+        elif self.config.type == "implicit-hate#implicit_hate": 
+            names = ['not implicit hate', 'implicit hate']
+        elif self.config.type == "implicit-hate#threatening_hate": 
+            names = ['not threatening hate', 'threatening hate']
+        elif self.config.type == "implicit-hate#irony_hate": 
+            names = ['not irony hate', 'irony hate']
+        elif self.config.type == "implicit-hate#other_hate": 
+            names = ['not other hate', 'other hate']
+        elif self.config.type == "implicit-hate#incitement_hate": 
+            names = ['not incitement hate', 'incitement hate']
+        elif self.config.type == "implicit-hate#inferiority_hate": 
+            names = ['not inferiority hate', 'inferiority hate']
+        elif self.config.type == "implicit-hate#stereotypical_hate": 
+            names = ['not stereotypical hate', 'stereotypical hate']
+        elif self.config.type == "implicit-hate#white_grievance_hate": 
+            names = ['not white grievance hate', 'white grievance hate']
+        elif self.config.type == "waseem_and_hovy#sexism": 
+            names = ['not sexism', 'sexism']
+        elif self.config.type == "waseem_and_hovy#racism": 
+            names = ['not racism', 'racism']
+        elif self.config.type == "humor-pairs": 
+            names = ['the first sentence is funnier', 'the second sentence is funnier']
+        elif self.config.type == "neutralizing-bias-pairs": 
+            names = ['the first sentence is biased', 'the second sentence is biased']
+        elif self.config.type == "same-side-pairs": 
+            names = ['not same side', 'same side']
+        elif self.config.type == "talkdown-pairs": 
+            names = ['not condescension', 'condescension']
+        elif self.config.type == "tweet_sentiment":
+            names = ["negative", "neutral", "positive"]
+        elif self.config.type == "tweet_offensive":
+            names = ["not offensive", "offensive"]
+        elif self.config.type == "tweet_irony":
+            names = ["not irony", "irony"]
+        elif self.config.type == "tweet_hate":
+            names = ["not hate", "hate"]
+        elif self.config.type == "tweet_emoji":
+            names = [
+                "❤",
+                "😍",
+                "😂",
+                "💕",
+                "🔥",
+                "😊",
+                "😎",
+                "✨",
+                "💙",
+                "😘",
+                "📷",
+                "🇺🇸",
+                "☀",
+                "💜",
+                "😉",
+                "💯",
+                "😁",
+                "🎄",
+                "📸",
+                "😜",
+            ]
+
+        elif self.config.type == "tweet_emotion":
+            names = ["anger", "joy", "optimism", "sadness"]
+        elif self.config.type == "emotion-span": 
+            names = ['cause']
+            label_type = datasets.Sequence(feature={n:datasets.Value(dtype='string', id=None) for n in names})
+            print(label_type)
+        elif self.config.type == "propaganda-span": 
+            names = ['propaganda']
+            label_type = datasets.Sequence(feature={n:datasets.Value(dtype='string', id=None) for n in names})
+        elif self.config.type == "toxic-span": 
+            names = ['toxic']
+            label_type = datasets.Sequence(feature={n:datasets.Value(dtype='string', id=None) for n in names})
+            
+        if self.config.type[-4:]=='span':
+            label_type = label_type#datasets.Sequence(feature={n:datasets.Value(dtype='string') for n in names})
+        elif len(names) > 1:
+            label_type = datasets.features.ClassLabel(names=names)
+        else:
+            label_type = datasets.Value("float32")
+        
+    
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {"text": datasets.Value("string"), 
+                 "label": label_type}
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        my_urls = _URLs[self.config.type]
+        data_dir = dl_manager.download_and_extract(my_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"text_path": data_dir["train_text"], "labels_path": data_dir["train_labels"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"text_path": data_dir["test_text"], "labels_path": data_dir["test_labels"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={"text_path": data_dir["val_text"], "labels_path": data_dir["val_labels"]},
+            ),
+        ]
+
+    def _generate_examples(self, text_path, labels_path):
+        """Yields examples."""
+
+        with open(text_path, encoding="utf-8") as f:
+            texts = f.readlines()
+            print(len(texts))
+        with open(labels_path, encoding="utf-8") as f:
+            labels = f.readlines()
+            print(len(labels))
+
+        for i, text in enumerate(texts):
+            yield i, {"text": text.strip(), "label": labels[i].strip() if self.config.type[-4:]!='span' else eval(labels[i])}