Datasets:
annotations_creators:
- expert-generated
language_creators:
- found
languages:
- zh
licenses:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: NLPCC Stance
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-classification-other-stance-detection
- sentiment-analysis
Dataset Card for "NLPCC 2016: Stance Detection in Chinese Microblogs"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: http://tcci.ccf.org.cn/conference/2016/pages/page05_evadata.html
- Repository:
- Paper: https://link.springer.com/chapter/10.1007/978-3-319-50496-4_85
- Point of Contact: Mads Kongsback
- Size of downloaded dataset files:
- Size of the generated dataset:
- Total amount of disk used:
Dataset Summary
This is a stance prediction dataset in Chinese. The data is that from a shared task, stance detection in Chinese microblogs, in NLPCC-ICCPOL 2016. It covers Task A, a mandatory supervised task which detects stance towards five targets of interest with given labeled data. Some instances of the dataset have been removed, as they were without label.
Supported Tasks and Leaderboards
- Stance Detection in Chinese Microblogs
Languages
Chinese, as spoken on the Weibo website (bcp47:zh)
Dataset Structure
Data Instances
Example instance:
{
'id': '0',
'target': 'IphoneSE',
'text': '3月31日，苹果iPhone SE正式开卖，然而这款小屏新机并未出现人们预想的疯抢局面。根据市场分析机构Localytics周一公布的数据，iPhone SE正式上市的这个周末，销量成绩并不算太好。',
'stance': 2
}
Data Fields
- id: a
stringfield with a unique id for the instance - target: a
stringrepresenting the target of the stance - text: a
stringof the stance-bearing text - stance: an
intrepresenting class label --0: AGAINST;1: FAVOR;2: NONE.
Data Splits
The training split has 2986 instances
Dataset Creation
Curation Rationale
The goal was to create a dataset of microblog text annotated for stance. Six stance targets were selected and data was collected from Sina Weibo for annotation.
Source Data
Initial Data Collection and Normalization
Not specified
Who are the source language producers?
Sina Weibo users
Annotations
Annotation process
The stance of each target-microblog pair is duplicated annotated by two students individually. If these two students provide the same annotation, the stance of this microblog-target pair is then labeled. If the different annotation is detected, the third student will be assigned to annotate this pair. Their annotation results will be voted to obtain the final label.
Who are the annotators?
Students in China
Personal and Sensitive Information
No reflections
Considerations for Using the Data
Social Impact of Dataset
The data preserves social media utterances verbatim and so has obviated any right to be forgotten, though usernames and post IDs are not explicitly included in the data.
Discussion of Biases
There'll be at least a temporal and regional bias to this data, as well as it only representing expressions of stance on six topics.
Other Known Limitations
Additional Information
Dataset Curators
The dataset is curated by the paper's authors.
Licensing Information
The authors distribute this data under Creative Commons attribution license, CC-BY 4.0.
Citation Information
@incollection{xu2016overview,
title={Overview of nlpcc shared task 4: Stance detection in chinese microblogs},
author={Xu, Ruifeng and Zhou, Yu and Wu, Dongyin and Gui, Lin and Du, Jiachen and Xue, Yun},
booktitle={Natural language understanding and intelligent applications},
pages={907--916},
year={2016},
publisher={Springer}
}