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๐Ÿ˜ƒ Sentiment Analysis on Free-Text Responses

Lucidya's AI analyzes Arabic and mixed language responses, categorizing feedback as positive, neutral, or negative with high accuracy and real-time insights for customer experience measurement.

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๐Ÿ˜Š Sentiment Analysis of Free-Text Responses

Lucidya offers advanced sentiment analysis for free-text responses with specialized support for over 15 Arabic dialects. Our solution combines cutting-edge AI engines and NLP modules to deliver highly accurate sentiment analysis in real-time across all your free-text feedback.

๐Ÿค” How It Works


This feature uses Lucidya's AI engines and models to provide sentiment analysis (feelings) categorized into three types:

  • ๐Ÿ™‚ Positive (N - %): Indicates customer satisfaction, approval, or happiness with the product/service.

  • ๐Ÿ˜ Neutral (N - %): Reflects balanced or impartial opinions without strong positive or negative sentiment.

  • ๐Ÿ™ Negative (N - %): Shows customer dissatisfaction, complaints, or disappointment with the experience.

Free-text responses' sentiment analysis

๐Ÿ“Š Sentiment Analysis Graph


๐Ÿ’ก Note

This graph provides an overall sentiment analysis for all free-text questions. If you have more than one question, the graph will display a comprehensive sentiment analysis combining all free-text responses.

The Sentiment Analysis graph offers the following features:

  1. Filter sentiment data by time period (Day, Week, Month, and Year).

  2. Switch between Linear and Logarithmic graph views.

  3. Export graph data as PNG or PDF file.

  4. Toggle visibility of sentiment types (๐ŸŸฉ Positive, ๐ŸŸง Neutral, and ๐ŸŸฅ Negative).

Filter Sentiment Analysis graph
Customize sentiment analysis graph by linear or logarithmic type
download sentiment analysis as a PNG or PDF

โ‰๏ธ FAQs


๐Ÿ‡ธ๐Ÿ‡ฆ How Accurate Is the Sentiment Analysis for Arabic Text?

Lucidya's sentiment analysis is highly accurate for Arabic text, with precision rates exceeding industry standards. Our specialized AI models are trained on vast Arabic language datasets and understand various dialects, slang, and cultural nuances.

โณ Can I Filter Responses by Sentiment Type?

Yes, you can filter responses by sentiment type (positive, neutral, negative) to focus on specific customer segments. This feature is available in the data exploration section of your dashboard.

๐ŸŒ Does Sentiment Analysis Work for Mixed Language Responses?

Yes, our system effectively analyzes sentiment in responses containing mixed languages, particularly Arabic-English code-switching, which is common in the MENA region.

โฑ๏ธ How Often Is the Sentiment Analysis Updated?

Sentiment analysis results are updated in real-time as new responses come in. The dashboard reflects the latest sentiment distribution across all your collected data.

๐Ÿงฉ Can I Integrate Sentiment Analysis with Other Reporting Tools?

Absolutely. Lucidya provides API access for enterprise customers to integrate sentiment analysis data with other business intelligence tools. Additionally, regular exports can be scheduled in various formats including CSV, Excel, and JSON.

๐Ÿ”‚ Is Historical Sentiment Data Available After System Updates?

Yes, all historical sentiment data is preserved when we update our AI models. In fact, when significant improvements are made to our sentiment analysis algorithms, you have the option to reprocess historical data with the new model for more accurate insights.

๐Ÿ”ก How Does the System Handle Sarcasm or Irony?

Our advanced NLP models are designed to detect contextual cues that indicate sarcasm or irony in text. The system analyzes patterns, sentiment contradictions, and linguistic markers to accurately categorize these nuanced expressions, particularly in Arabic contexts.

๐Ÿ˜ƒ Can I Customize the Sentiment Categories?

Currently, the sentiment analysis uses the standard three categories (positive, neutral, negative). However, enterprise users can work with our team to customize sentiment thresholds or add subcategories based on specific business needs.

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