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Singapore airlines reviews
Aerospace and Aviation
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About
This dataset captures customer feedback for Singapore Airlines based on user reviews from various platforms. It provides insights into the customer experience, including service quality, seat comfort, food, and staff behaviour. The dataset includes structured fields that can be used to analyse customer satisfaction, identify pain points, and benchmark airline performance.
Dataset Features:
- S_ID: A unique identifier for each review.
- Published Date: The date and time when the review was published, formatted as ISO 8601.
- Published Platform: The platform or device from which the review was published (e.g., Desktop, Mobile).
- Rating: The numerical rating provided by the reviewer, typically ranging from 0 to 5.
- Type: Indicates the type of feedback, e.g., "review."
- Text: The detailed review content provided by the user describes their experience.
- Title: A short, descriptive summary of the review.
- Helpful Votes: The number of users who found the review helpful.
Usage:
This dataset is valuable for:
- Sentiment Analysis: Understanding customer satisfaction and sentiment trends.
- Topic Modeling: Identifying common themes or issues in customer reviews.
- Predictive Analytics: Forecasting customer ratings based on review content.
- Service Improvement: Pinpointing areas for operational or service enhancements.
Coverage:
The dataset provides a comprehensive view of customer experiences across different dates, platforms, and review ratings. It captures both positive and negative feedback, offering a balanced dataset for various analytical purposes.
License:
CC0 (Public Domain)
Who Can Use It:
This dataset is suitable for data scientists, machine learning practitioners, researchers, airline industry analysts, and students interested in customer feedback analysis.
How to Use It:
- Develop text classification models to predict ratings or review helpfulness.
- Perform natural language processing (NLP) tasks to extract key insights.
- Create dashboards or visualisations to monitor customer satisfaction trends.
- Benchmark airline performance by comparing it with reviews from competitors.
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