windaan/autotrain-data-ta-winda-ota-sentiment-analysis

该数据集是为项目ta-winda-ota-sentiment-analysis自动处理的AutoTrain数据集，主要用于文本分类任务。数据集包含用户评论及其相关元数据，如评论ID、用户名、用户图像、评论内容、目标评分等。数据集的BCP-47语言代码为unk，表示语言未知。数据集被分为训练集和验证集，分别包含2826和709个样本。

原始信息汇总

AutoTrain Dataset for project: ta-winda-ota-sentiment-analysis

数据集描述

该数据集由AutoTrain自动处理，用于项目ta-winda-ota-sentiment-analysis。

语言

数据集的语言BCP-47代码为unk。

数据集结构

数据实例

数据集的一个样本如下所示：

json [ { "feat_reviewId": "11e13237-0fe6-40ae-b035-e6d6d0287a80", "feat_userName": "Sulaiman", "feat_userImage": "https://play-lh.googleusercontent.com/a-/AD_cMMQbSKYMfa0BWeV5LYPf0kZ1MV3PKx_VgYzByqUb5Q", "text": "ok", "target": 4, "feat_thumbsUpCount": 0, "feat_reviewCreatedVersion": "3.77.1", "feat_at": "2023-05-27 01:49:05", "feat_replyContent": "Hi, we are so grateful to get a lot of support from you. Hope you continue to enjoy our offers. If you have any feedback or suggestions, let us know on https://www.traveloka.com/contactus, our customer service would love to serve you in 24 hours. Thank you!", "feat_repliedAt": "2023-05-27 02:12:14", "feat_appVersion": "3.77.1", "feat_sortOrder": "newest", "feat_appId": "com.traveloka.android" }, { "feat_reviewId": "671f8bed-8371-490f-bc33-51034fc798f3", "feat_userName": "Feri Yadi", "feat_userImage": "https://play-lh.googleusercontent.com/a-/AD_cMMT7JhwvdqMkI84xvo_4HZ-2xV04Pvsn75E_SD3GoQ", "text": "ok", "target": 0, "feat_thumbsUpCount": 0, "feat_reviewCreatedVersion": "10.37.0", "feat_at": "2023-05-08 02:38:38", "feat_replyContent": "We apologize for any inconvenience this has caused you. Your experience is important to us. If there is something more we can help you with,

please write an email to [e-mail] and include your phone number if you would prefer to be contacted by phone.

Our team will review the information and contact you back as soon as possible.", "feat_repliedAt": "2023-05-08 05:14:09", "feat_appVersion": "10.37.0", "feat_sortOrder": "newest", "feat_appId": "com.agoda.mobile.consumer" } ]

数据集字段

数据集包含以下字段（也称为“特征”）：

json { "feat_reviewId": "Value(dtype=string, id=None)", "feat_userName": "Value(dtype=string, id=None)", "feat_userImage": "Value(dtype=string, id=None)", "text": "Value(dtype=string, id=None)", "target": "ClassLabel(names=[1, 2, 3, 4, 5], id=None)", "feat_thumbsUpCount": "Value(dtype=int64, id=None)", "feat_reviewCreatedVersion": "Value(dtype=string, id=None)", "feat_at": "Value(dtype=string, id=None)", "feat_replyContent": "Value(dtype=string, id=None)", "feat_repliedAt": "Value(dtype=string, id=None)", "feat_appVersion": "Value(dtype=string, id=None)", "feat_sortOrder": "Value(dtype=string, id=None)", "feat_appId": "Value(dtype=string, id=None)" }

数据集拆分

该数据集被拆分为训练集和验证集。拆分大小如下：

拆分名称	样本数量
train	2826
valid	709