task_categories:text-classification language:en language:fr language:ja language:it language:de license:cc-by-nc-nd-4.0 code finance region:us
---
license: cc-by-nc-nd-4.0
task_categories:
- text-classification
language:
- en
- fr
- ja
- it
- de
tags:
- code
- finance
---

# Reviews on Messengers Dataset 🤳 ⭐️

The Reviews on Messengers Dataset is a comprehensive collection of **200** the most recent customer reviews on **6** messengers obtained from the popular app store, **Google Play**. See the list of the apps below.
This dataset encompasses reviews written in **5** different languages: English, French, German, Italian, Japanese.

The dataset's multilingual nature makes it useful for natural language processing tasks, sentiment analysis algorithms, and other machine learning applications that require diverse language data for training and evaluation.

The dataset can be highly valuable in training and fine-tuning machine learning models to automatically classify sentiments, predict customer satisfaction, or extract key information from customer reviews. 

The data was scraped with `google-play-scraper` python lib by [TrainingData Team](https://trainingdata.pro/data-market?utm_source=kaggle&utm_medium=cpc&utm_campaign=6000-messengers-reviews-google-play).

### Apps in the dataset and their IDs: 
- Telegram: `'org.telegram.messenger'`,
- Facebook Messenger: `'com.facebook.orca'`,
- Whats App: `'com.whatsapp'`,
- Viber: `'com.viber.voip'`,
- Snapchat: `'com.snapchat.android'`,
- We Chat: `'com.tencent.mm'`.

### Languages in the dataset:
- English: `EN`,
- French: `FR`,
- German: `DE`,
- Italian : `IT`,
- Japanese: `JP`

# Content
For each item, we extracted:
- **reviewId**: ID of the review,
- **userName**: name of the reviewer,
- **userImage**: profile image of the reviewer,
- **content**: text of the review,
- **score**: number of stars given to the review,
- **thumbsUpCount**: number of likes on the review,
- **at**: date of the review,
- **replyContent**: text of the developer's comment,
- **repliedAt**: date of the developer's comment,
- **appVersion**: version of the app,
- **userLang**: language of the review,
- **app_id**: ID of the app

# Try to find the messenger with the most attentive support 😉

## **[TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=messengers-reviews-google-play)** provides high-quality data annotation tailored to your needs

More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets**

TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**