// Documentation template for copyright protection
const emojiCopyrightDocumentation = {
    basicInfo: {
        title: "Custom Emoji Design",
        creator: "Designer Name",
        creationDate: "2025-09-07",
        firstPublication: "2025-09-07",
        registrationStatus: "pending" // or "registered", "unregistered"
    },
    
    creativeElements: {
        originalArtwork: true,
        colorScheme: "original palette design",
        characterDesign: "unique facial features and expression",
        stylization: "distinctive art style elements",
        composition: "original arrangement of visual elements"
    },
    
    derivativeElements: {
        publicDomainElements: ["basic geometric shapes"],
        licensedElements: [],
        fairUseElements: []
    },
    
    usage: {
        commercial: false,
        platforms: ["Discord", "Slack", "Telegram"],
        licensingTerms: "All rights reserved"
    }
};

// Trademark classification system for emojis
const emojiTrademarkClasses = {
    class009: {
        description: "Computer software, mobile applications",
        emojiUse: "App icons, software interface elements",
        examples: ["messaging app emoji sets", "game character emojis"]
    },
    
    class035: {
        description: "Advertising and business services",
        emojiUse: "Brand identification in marketing materials",
        examples: ["corporate branded emojis", "promotional campaign symbols"]
    },
    
    class041: {
        description: "Entertainment services",
        emojiUse: "Entertainment content identification",
        examples: ["streaming service emojis", "gaming platform symbols"]
    },
    
    class042: {
        description: "Computer services and software design",
        emojiUse: "Technical service identification",
        examples: ["cloud service emojis", "API service symbols"]
    }
};

# Risk assessment framework for character-based emojis
class CharacterInfringementRisk:
    def __init__(self):
        self.risk_factors = {
            'popularity': 0,      # 1-10 scale
            'recent_creation': 0, # Years since creation
            'active_enforcement': 0, # Known enforcement activity
            'distinctive_features': 0, # Uniqueness of visual elements
            'commercial_value': 0  # Economic importance to owner
        }
    
    def assess_risk_level(self, character_info):
        """Calculate overall infringement risk"""
        risk_score = 0
        
        # High popularity increases risk
        risk_score += character_info['popularity'] * 2
        
        # Recent creations have stronger protection
        if character_info['creation_year'] > 1990:
            risk_score += 5
        
        # Active enforcement history
        risk_score += character_info['enforcement_cases'] * 3
        
        # Highly distinctive characters are riskier to copy
        risk_score += character_info['distinctiveness'] * 1.5
        
        if risk_score > 50:
            return "HIGH_RISK"
        elif risk_score > 25:
            return "MEDIUM_RISK"
        else:
            return "LOW_RISK"
    
    def generate_recommendations(self, risk_level, character_info):
        """Provide risk mitigation recommendations"""
        recommendations = []
        
        if risk_level == "HIGH_RISK":
            recommendations.extend([
                "Avoid creating emoji based on this character",
                "Consider creating original character inspired by general concept",
                "Seek legal counsel before proceeding",
                "Explore licensing opportunities with rights holder"
            ])
        elif risk_level == "MEDIUM_RISK":
            recommendations.extend([
                "Significantly modify distinctive features",
                "Focus on general concepts rather than specific character traits",
                "Document creative process to show independent creation",
                "Consider fair use analysis with legal counsel"
            ])
        else:
            recommendations.extend([
                "Still exercise caution and document originality",
                "Avoid using character names or direct references",
                "Focus on transformative elements"
            ])
        
        return recommendations

## Apple vs. Pear Computer (Hypothetical Emoji Case)

**Facts:**
- Developer created custom emoji featuring fruit company logo
- Used in business messaging platform
- Company claimed trademark infringement

**Legal Issues:**
1. Trademark infringement in commerce
2. Likelihood of confusion among consumers  
3. Dilution of famous trademark
4. Fair use or parody defenses

**Outcome Factors:**
- Commercial vs. non-commercial use
- Degree of similarity to original mark
- Context of use and consumer perception
- Transformative nature of the work

**Lessons Learned:**
- Even small emoji uses can trigger trademark claims
- Context matters significantly in infringement analysis
- Commercial use dramatically increases risk
- Documentation of creative process is crucial

// Platform content moderation system for custom emojis
class EmojiContentModeration {
    constructor() {
        this.automatedChecks = [
            'visualSimilarityDetection',
            'metadataAnalysis',
            'userReportingSystem',
            'proactiveScanning'
        ];
        
        this.humanReview = {
            required: true,
            triggers: ['automated_flag', 'user_report', 'copyright_claim'],
            reviewers: ['content_moderators', 'legal_team']
        };
    }
    
    async moderateEmojiUpload(emoji, userInfo) {
        const flags = await this.runAutomatedChecks(emoji);
        
        if (flags.length > 0) {
            return await this.flagForReview(emoji, flags, userInfo);
        }
        
        return { approved: true, message: "Emoji approved for upload" };
    }
    
    async runAutomatedChecks(emoji) {
        const flags = [];
        
        // Visual similarity to known copyrighted works
        const similarityResults = await this.checkVisualSimilarity(emoji);
        if (similarityResults.confidence > 0.8) {
            flags.push({
                type: 'copyright_similarity',
                confidence: similarityResults.confidence,
                matches: similarityResults.matches
            });
        }
        
        // Metadata analysis for problematic keywords
        const metadataFlags = await this.analyzeMetadata(emoji);
        flags.push(...metadataFlags);
        
        return flags;
    }
}

# Trademark application tracking system
class EmojiTrademarkApplication:
    def __init__(self):
        self.application_stages = [
            'initial_search',
            'application_filing',
            'examination',
            'publication',
            'opposition_period',
            'registration'
        ]
        
        self.required_documentation = {
            'specimen_of_use': 'Evidence of emoji use in commerce',
            'description_of_goods': 'Detailed service/product description', 
            'drawing_of_mark': 'Clear representation of emoji design',
            'filing_basis': 'Use in commerce or intent to use',
            'classification': 'Appropriate international class designation'
        }
    
    def prepare_application(self, emoji_info):
        """Prepare comprehensive trademark application"""
        application = {
            'applicant_info': emoji_info['creator'],
            'mark_info': {
                'mark_drawing': emoji_info['design_file'],
                'mark_description': emoji_info['description'],
                'color_claim': emoji_info.get('color_significance', False),
                'design_elements': emoji_info['visual_elements']
            },
            'goods_services': self.classify_goods_services(emoji_info['usage']),
            'filing_basis': self.determine_filing_basis(emoji_info['commercial_use']),
            'priority_claims': emoji_info.get('foreign_applications', [])
        }
        
        return application
    
    def classify_goods_services(self, usage_info):
        """Determine appropriate trademark classifications"""
        classifications = []
        
        if 'software' in usage_info:
            classifications.append({
                'class': 9,
                'description': 'Computer software featuring custom emoji designs'
            })
        
        if 'messaging_services' in usage_info:
            classifications.append({
                'class': 38,
                'description': 'Electronic messaging services featuring custom emojis'
            })
        
        if 'merchandise' in usage_info:
            classifications.append({
                'class': 25,
                'description': 'Clothing featuring emoji designs'
            })
        
        return classifications

## Sample EULA Provisions for Custom Emojis

### Granted Rights:
- Personal, non-commercial use in digital communications
- Use within licensed platforms and applications
- Modification for personal use only

### Restrictions:
- No redistribution or resale of emoji designs
- No use in competing emoji creation platforms
- No removal of attribution or copyright notices
- No creation of derivative works for commercial purposes

### Duration and Termination:
- License effective until terminated
- Automatic termination upon violation of terms
- Survival of restrictions post-termination

// Commercial licensing agreement framework
const commercialLicenseFramework = {
    grantedRights: {
        scope: "worldwide / regional / limited territory",
        exclusivity: "exclusive / non-exclusive / limited exclusive",
        fields: ["advertising", "merchandise", "digital_platforms", "print_media"],
        duration: "perpetual / term_limited / renewable",
        modifications: "permitted / restricted / prohibited"
    },
    
    financialTerms: {
        upfrontFee: "fixed payment upon execution",
        royalties: "percentage of revenue / per-use fees",
        minimumGuarantees: "minimum annual payments",
        auditRights: "licensee audit and reporting requirements",
        paymentSchedule: "monthly / quarterly / annual"
    },
    
    qualityControl: {
        approvalRights: "licensor approval of emoji usage",
        brandGuidelines: "compliance with visual standards",
        qualityStandards: "minimum technical specifications",
        reviewProcess: "pre-publication review requirements"
    },
    
    intellectualProperty: {
        ownershipRetention: "licensor retains all rights",
        improvements: "ownership of derivative works",
        infringementDefense: "responsibilities for IP enforcement",
        indemnification: "protection against third-party claims"
    },
    
    termination: {
        triggers: ["material_breach", "insolvency", "change_of_control"],
        notice: "written notice requirements and cure periods",
        consequences: "immediate cessation / wind-down period",
        survival: "provisions that survive termination"
    }
};

# Revenue optimization model for emoji licensing
class EmojiLicensingRevenue:
    def __init__(self):
        self.pricing_models = {
            'per_use': {
                'base_rate': 0.001,  # $0.001 per use
                'volume_discounts': {
                    1000: 0.0008,     # $0.0008 for 1K+ uses
                    10000: 0.0005,    # $0.0005 for 10K+ uses
                    100000: 0.0003    # $0.0003 for 100K+ uses
                }
            },
            
            'subscription': {
                'individual': 4.99,      # $4.99/month
                'business': 19.99,       # $19.99/month
                'enterprise': 99.99      # $99.99/month
            },
            
            'one_time': {
                'personal': 9.99,        # $9.99 one-time
                'commercial': 99.99,     # $99.99 one-time
                'exclusive': 999.99      # $999.99 exclusive rights
            }
        }
    
    def calculate_optimal_pricing(self, usage_data, market_data):
        """Determine optimal pricing strategy"""
        projected_revenue = {}
        
        for model, pricing in self.pricing_models.items():
            revenue = self.project_revenue(model, pricing, usage_data, market_data)
            projected_revenue[model] = revenue
        
        return max(projected_revenue.items(), key=lambda x: x[1])
    
    def project_revenue(self, model, pricing, usage_data, market_data):
        """Project revenue for specific pricing model"""
        if model == 'per_use':
            return self.calculate_per_use_revenue(pricing, usage_data)
        elif model == 'subscription':
            return self.calculate_subscription_revenue(pricing, market_data)
        elif model == 'one_time':
            return self.calculate_one_time_revenue(pricing, market_data)

## International Licensing Checklist

### Legal Framework:
- [ ] Governing law selection
- [ ] Dispute resolution mechanism
- [ ] Jurisdiction for legal proceedings
- [ ] Compliance with local IP laws

### Commercial Terms:
- [ ] Currency designation and exchange rate handling
- [ ] Tax obligations and withholding requirements
- [ ] Import/export restrictions
- [ ] Local partnership requirements

### Cultural Adaptation:
- [ ] Local content review and approval processes
- [ ] Cultural sensitivity compliance
- [ ] Language localization requirements
- [ ] Religious or political content restrictions

### Technical Integration:
- [ ] Platform compatibility across regions
- [ ] Technical support and maintenance
- [ ] Data privacy and security compliance
- [ ] Local hosting or data residency requirements

# Automated infringement detection and response system
class EmojiInfringementDetection:
    def __init__(self):
        self.monitoring_sources = [
            'social_media_platforms',
            'e_commerce_sites', 
            'mobile_applications',
            'web_scraping_bots',
            'user_reports'
        ]
        
        self.response_protocols = {
            'level_1': 'automated_takedown_notice',
            'level_2': 'cease_and_desist_letter', 
            'level_3': 'legal_action_initiation'
        }
    
    async def scan_for_infringement(self, protected_emojis):
        """Scan multiple sources for potential infringement"""
        findings = []
        
        for source in self.monitoring_sources:
            results = await self.scan_source(source, protected_emojis)
            findings.extend(results)
        
        return self.analyze_and_prioritize(findings)
    
    def analyze_and_prioritize(self, findings):
        """Analyze findings and prioritize enforcement actions"""
        prioritized = []
        
        for finding in findings:
            risk_score = self.calculate_risk_score(finding)
            response_level = self.determine_response_level(risk_score)
            
            prioritized.append({
                'finding': finding,
                'risk_score': risk_score,
                'recommended_action': response_level,
                'urgency': 'high' if risk_score > 70 else 'medium' if risk_score > 40 else 'low'
            })
        
        return sorted(prioritized, key=lambda x: x['risk_score'], reverse=True)