Poleval2019_사이버불링

참고자료:

• 암호
• 포옹하는 얼굴

task01

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:poleval2019_cyberbullying/task01')

• 설명 :

In Task 6-1, the participants are to distinguish between normal/non-harmful tweets (class: 0) and tweets
    that contain any kind of harmful information (class: 1). This includes cyberbullying, hate speech and
    related phenomena.

    In Task 6-2, the participants shall distinguish between three classes of tweets: 0 (non-harmful),
    1 (cyberbullying), 2 (hate-speech). There are various definitions of both cyberbullying and hate-speech,
    some of them even putting those two phenomena in the same group. The specific conditions on which we based
    our annotations for both cyberbullying and hate-speech, which have been worked out during ten years of research
    will be summarized in an introductory paper for the task, however, the main and definitive condition to 1
    distinguish the two is whether the harmful action is addressed towards a private person(s) (cyberbullying),
    or a public person/entity/large group (hate-speech).

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.0.0
• 분할 :

나뉘다	예
'test'	1000
'train'	10041

• 특징 :

{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 2,
        "names": [
            "0",
            "1"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}

task02

TFDS에 이 데이터세트를 로드하려면 다음 명령어를 사용하세요.

ds = tfds.load('huggingface:poleval2019_cyberbullying/task02')

• 설명 :

In Task 6-1, the participants are to distinguish between normal/non-harmful tweets (class: 0) and tweets
    that contain any kind of harmful information (class: 1). This includes cyberbullying, hate speech and
    related phenomena.

    In Task 6-2, the participants shall distinguish between three classes of tweets: 0 (non-harmful),
    1 (cyberbullying), 2 (hate-speech). There are various definitions of both cyberbullying and hate-speech,
    some of them even putting those two phenomena in the same group. The specific conditions on which we based
    our annotations for both cyberbullying and hate-speech, which have been worked out during ten years of research
    will be summarized in an introductory paper for the task, however, the main and definitive condition to 1
    distinguish the two is whether the harmful action is addressed towards a private person(s) (cyberbullying),
    or a public person/entity/large group (hate-speech).

• 라이센스 : 알려진 라이센스 없음
• 버전 : 1.0.0
• 분할 :

나뉘다	예
'test'	1000
'train'	10041

• 특징 :

{
    "text": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "num_classes": 3,
        "names": [
            "0",
            "1",
            "2"
        ],
        "names_file": null,
        "id": null,
        "_type": "ClassLabel"
    }
}