SaudiShopInsights Dataset: Saudi Customer Reviews in Clothes and Electronics

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razan alrefaey
Last updated:
Tue, 12/19/2023 - 16:50
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The SaudiShopInsights dataset is a comprehensive collection of customer reviews in the Arabic language, specifically focusing on the Saudi dialect, within the domains of fashion and electronics. Gathered from various online platforms, this dataset serves as a valuable resource for researchers and practitioners interested in sentiment analysis, natural language processing, and customer behavior studies. The dataset encompasses a diverse range of opinions, sentiments, and preferences expressed by consumers, providing insights into their experiences with products and services in the clothing and electronics sectors. Researchers can leverage this dataset to develop and enhance models for sentiment analysis, customer feedback analysis, and other applications in the domain of Arabic language processing. The SaudiShopInsights dataset offers a unique perspective on consumer sentiments, contributing to a deeper understanding of market trends and enabling advancements in customer-centric analytics.


SaudiShopInsights Dataset Documentation


The SaudiShopInsights dataset is a valuable resource for researchers and analysts interested in exploring customer sentiments in the Arabic language, with a specific focus on the Saudi dialect. This documentation provides a guide on how to effectively utilize the dataset, which is structured as an Excel file.

Dataset Format:

The dataset is stored in an Excel file, with each row representing a unique customer review. The primary column, labeled "Review," contains the textual feedback provided by customers. Additionally, there are multiple columns corresponding to various aspects related to the fashion and electronics sectors.

Column Definitions:

  1. Review:
    • Description: Textual feedback provided by customers.
    • Data Type: Text (String)
  2. Clothes Aspects:
    • Columns: Aspects related to the fashion sector, such as "Style," "Fabric," "Size," etc.
    • Data Type: Numeric and None
  3. Electronics Aspects:
    • Columns: Aspects related to the electronics sector, such as "Price," "Quality," "Usage," etc.
    • Data Type: Numeric and None

Utilizing the Dataset:

  1. Exploratory Data Analysis (EDA):
    • Conduct EDA to understand the distribution of sentiments in customer reviews.
    • Explore the frequency and distribution of ratings for different aspects.
  2. Sentiment Analysis:
    • Leverage the "Review" column for sentiment analysis using natural language processing techniques.
    • Utilize the aspect-specific columns for targeted sentiment analysis in fashion and electronics.
  3. Aspect-based Analysis:
    • Analyze specific aspects (e.g., design, quality, performance) by aggregating  sentiments.
  4. Training Machine Learning Models:
  • Train models for sentiment prediction based on customer reviews.
  • Use the aspect-related columns as features for training sector-specific models.


  • Ensure proper data preprocessing and cleaning before conducting analyses.
  • Respect ethical considerations and privacy guidelines when using customer reviews.

By following this documentation, researchers and analysts can effectively leverage the SaudiShopInsights dataset to gain valuable insights into customer sentiments in the domains of fashion and electronics.



Submitted by FIRDAOUS AIT MOHAMED on Thu, 04/11/2024 - 12:56