Articles Extraction & Text Analysis Pipeline

Solution & Approach

• URL Discovery & Link Extraction: Built BlackCoffer_link_extract.py to systematically crawl and discover article URLs from the main website and category pages. Implemented intelligent URL filtering to identify valid article links while avoiding duplicates, media files, and external links. Created URL queue management system with retry logic for failed requests
• Paragraph-Level Content Extraction: Developed BlackCoffer_paragraph_extract.py using BeautifulSoup to extract clean article text while preserving structure. Implemented smart content detection to identify main article body, removing navigation, ads, and footer content. Preserved paragraph boundaries and heading hierarchy for accurate text analysis. Handled various article formats and layouts with adaptive parsing rules
• Text Preprocessing & Cleaning: Removed HTML tags, special characters, and formatting artifacts while preserving sentence structure. Normalized Unicode characters and handled encoding issues for consistent text processing. Implemented stop word removal using custom business-domain dictionary. Applied text tokenization maintaining sentence and paragraph boundaries for context-aware analysis
• Sentiment Analysis & Polarity Scoring: Calculated positive/negative sentiment scores using financial and business lexicons. Implemented subjectivity analysis to distinguish factual reporting from opinion pieces. Created polarity distribution metrics across articles to identify sentiment trends. Developed confidence scoring for sentiment predictions based on text clarity and lexicon coverage
• Readability & Complexity Metrics: Computed Flesch Reading Ease scores to assess article accessibility for target audiences. Calculated average sentence length, syllables per word, and complex word percentage. Generated Gunning Fog Index for determining years of education needed to understand content. Created custom complexity score combining multiple readability formulas for comprehensive assessment
• Linguistic Feature Analysis: Extracted average word length, sentence count, and paragraph structure metrics. Identified personal pronouns usage to measure article objectivity and engagement style. Calculated word diversity using type-token ratio for vocabulary richness analysis. Detected passive voice percentage and other stylistic elements affecting readability
• Structured Output Generation: Created Excel output following Output_Data_Structure.xlsx specifications with all computed metrics. Implemented CSV export for database integration and further analysis workflows. Generated JSON format for API consumption and dashboard integration. Added metadata including extraction timestamp, source URL, and processing status