Air France Reviews Dataset

The Air France Reviews Dataset is a collection of customer reviews specifically curated to analyze feedback on Air France services. This dataset was ethically mined using apify.com, ensuring compliance with web scraping guidelines and ethical standards. Additionally, all personally identifiable information (PII) has been thoroughly removed to protect user privacy, making it safe for further analysis and application in data-driven projects.

Dataset Columns
The dataset includes several key columns:

Review Text: The main text of the review, capturing the customer’s opinion.
Rating: The numerical rating given by the customer, typically ranging from 1 to 5.
Review Date: The date on which the review was posted.
Sentiment: An automatic or manually annotated field that indicates the review's sentiment (e.g., positive, negative, neutral).
Review Source: The platform or website from which the review was gathered (if applicable).
Language: The language of the review, helpful for multilingual analysis.
Applications in NLP Analysis
This dataset is well-suited for Natural Language Processing (NLP) tasks, allowing for in-depth analysis of customer sentiment, common complaints, frequently praised aspects, and trends in customer satisfaction over time. Examples of NLP applications include:

Sentiment Analysis: Determining the general mood of customers.
Topic Modeling: Identifying recurrent themes or issues in customer reviews.
Emotion Detection: Understanding specific emotions, such as frustration or satisfaction.
Keyword Extraction: Finding essential terms related to service, comfort, punctuality, etc.
This dataset has a fixed frequency of updates, meaning it is not continuously updated and remains static. It is an ideal resource for exploratory and project-based analysis rather than for monitoring live feedback.

Column Descriptions
| Review Text| Contains the main text of each customer review, providing feedback on their experience with Air France. |
|Rating |Numerical rating assigned by the customer, usually on a scale of 1 to 5, with 5 being the highest.|
| Review Date |The date when the review was posted, formatted as YYYY-MM-DD. |
| Sentiment | Indicates the sentiment of the review, such as positive, neutral, or negative. |
| Review Source | Specifies the platform or website where the review was obtained. |
|Language|The language in which the review was written, useful for multilingual analysis.