Enterprise AI Analysis
Unveiling Persian Market Dynamics: A Comprehensive Analysis of Consumer Demand Using NLP Techniques with Explainable Artificial Intelligence
This research addresses challenges in Persian Natural Language Processing (NLP) by applying advanced NLP techniques, including sentiment analysis, named entity recognition (NER), and gender prediction, to analyze market demand. Leveraging the fine-tuned ParsBERT model, the study achieved an impressive 98% accuracy in sentiment classification, significantly outperforming other machine learning and deep learning models. Furthermore, Explainable AI (XAI) methods (LIME and SHAP) were integrated to provide transparency into the model's decision-making process. The analysis revealed consumer preferences for laptop brands, with Lenovo, Dell, and HP being the most preferred. This comprehensive approach offers critical insights for businesses and policymakers targeting the Farsi-speaking market, facilitating informed strategic decisions.
Executive Impact
Key performance indicators from the research demonstrate significant advancements and potential for enterprise application.
0%
ParsBERT Sentiment Accuracy
0M+
Global Persian Speakers
0th
Persian Language Global Rank
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Unveiling Persian Market Dynamics: NLP & Explainable AI for Consumer Demand
The Persian language, spoken by over 110 million people, faces NLP development challenges due to limited datasets and complex linguistics. This study pioneers the application of advanced NLP, including sentiment analysis, NER, and gender prediction, to unlock consumer insights in this significant market. By leveraging sophisticated models like ParsBERT and integrating Explainable AI, we offer unparalleled transparency and actionable intelligence for businesses and policymakers.
Robust Data Collection & Preprocessing
Our methodology began with automatic data scraping from YouTube and Facebook for laptop-related comments, supplemented with Urdu data translated into Persian. Laptop brand and model names were extracted from Wikipedia. A dictionary-based NER system was implemented to handle brand variations. Data cleaning involved removing emojis, URLs, and special characters, followed by tokenization and stemming using the Hazm NLP Toolkit. The cleaned data was manually labeled for sentiment (positive, negative, neutral) by native Persian speakers. Gender prediction was performed using the Python gender guesser library, with Persian names translated to English via Google Cloud Translation API. The dataset was split 80% for training and 20% for testing.
Superior Sentiment Analysis & Consumer Insights
The fine-tuned ParsBERT model achieved an outstanding 98% accuracy in sentiment classification, outperforming traditional ML models like Multinomial LR (92%), SVM (91%), and deep learning models like CNN (92%) and LSTM (91%). The integration of LIME and SHAP provided critical insights into the model's decision-making, highlighting feature importance for sentiment predictions. Demand analysis revealed Lenovo as the most preferred laptop brand among both male and female consumers, closely followed by Dell, HP, Apple, Asus, and Acer. These findings offer valuable, transparent insights into the Farsi-speaking market.
98%
Sentiment Analysis Accuracy with ParsBERT
Enterprise Process Flow
Social Media Comments Scraping
→
Laptop Brand Name Scraping
→
Data Cleaning & Preprocessing
→
Manual Sentiment Annotation
→
Gender Prediction
→
Named Entity Recognition
→
Sentiment Analysis
→
Explainable AI (LIME & SHAP)
| Model | Precision | Recall | F-1 Score | Accuracy |
|---|---|---|---|---|
| Multinomial LR | 91 | 91 | 92 | 92 |
| SVM | 92 | 91 | 91 | 91 |
| Multinomial NB | 89 | 89 | 89 | 89 |
| Random Forest | 93 | 91 | 91 | 91 |
| Gradient Boosting | 89 | 88 | 88 | 88 |
| RNN | 91 | 91 | 91 | 91 |
| CNN | 92 | 92 | 92 | 92 |
| LSTM | 91 | 91 | 91 | 91 |
| ParsBERT | 99 | 98 | 98 | 98 |
Impact on Farsi-Speaking Market Strategy
The insights derived from this study offer significant strategic advantages for businesses operating or planning to enter the Farsi-speaking market. By accurately identifying consumer preferences and sentiment towards specific laptop brands like Lenovo, Dell, and HP, companies can tailor product development, marketing campaigns, and customer service initiatives. The 98% accuracy in sentiment analysis, combined with explainable AI, allows for data-driven decision-making, optimizing market entry strategies and enhancing competitive advantage. Understanding gender-based demand variations further refines segmentation, ensuring marketing efforts resonate deeply with target demographics and fostering strong brand loyalty in a complex linguistic landscape.
Calculate Your Potential AI ROI
Estimate the transformative impact of AI on your enterprise by adjusting key variables. See how operational efficiency translates into substantial savings and reclaimed hours.
Annual Savings Potential
Annual Hours Reclaimed
AI Implementation Roadmap
A typical phased approach to integrate advanced AI solutions into your enterprise operations.
Phase 1: Discovery & Strategy
Conduct in-depth analysis of current systems, identify AI opportunities, define project scope, and establish clear KPIs.
Phase 2: Data Engineering & Model Training
Collect, clean, and prepare data. Select and train appropriate AI/ML models based on strategic objectives.
Phase 3: Integration & Pilot Deployment
Seamlessly integrate AI models into existing workflows and test performance in a controlled pilot environment.
Phase 4: Optimization & Scaling
Refine models based on pilot feedback, ensure scalability, and roll out AI solutions across the enterprise.
Phase 5: Monitoring & Continuous Improvement
Implement ongoing monitoring, performance tracking, and iterative updates to maintain peak AI efficiency and adapt to evolving needs.
Ready to Transform Your Enterprise with AI?
Leverage cutting-edge AI research to drive innovation and efficiency. Our experts are ready to guide your next steps.
Ready to Get Started?
Book Your Free Consultation.
Let's Discuss Your AI Strategy!
Lets Discuss Your Needs
Select a Date
Sun
Mon
Tue
Wed
Thu
Fri
Sat