""" 视频内容分析框架 用于分析心理学/恋爱技巧类视频内容 """ import json from pathlib import Path class VideoContentAnalyzer: def __init__(self, video_title): self.video_title = video_title self.analysis = { "title": video_title, "category": self._determine_category(), "key_concepts": [], "core_principles": [], "practical_techniques": [], "psychological_insights": [], "controversial_points": [], "ethical_considerations": [], "key_quotes": [], "summary": "", } def _determine_category(self): """根据标题确定视频类别""" title_lower = self.video_title.lower() categories = { "relationship_psychology": ["爱", "恋爱", "女人", "男人", "感情", "关系"], "self_improvement": ["方法", "技巧", "提升", "改变"], "controversial": ["脏", "强行", "套路", "操控"], "educational": ["心理学", "心理", "科学", "研究"], } detected = [] for cat, keywords in categories.items(): for kw in keywords: if kw in title_lower: detected.append(cat) break return detected if detected else ["unknown"] def analyze_transcript(self, transcript_text): """分析转录文本""" print(f"分析视频: {self.video_title}") print(f"类别: {', '.join(self.analysis['category'])}") print(f"转录长度: {len(transcript_text)} 字符") # 提取关键概念 self._extract_key_concepts(transcript_text) # 提取核心原则 self._extract_core_principles(transcript_text) # 提取实用技巧 self._extract_practical_techniques(transcript_text) # 提取心理学洞察 self._extract_psychological_insights(transcript_text) # 识别争议点 self._identify_controversial_points(transcript_text) # 伦理考量 self._analyze_ethical_considerations(transcript_text) # 提取关键引述 self._extract_key_quotes(transcript_text) # 生成总结 self._generate_summary(transcript_text) return self.analysis def _extract_key_concepts(self, text): """提取关键概念""" # 这里可以添加更复杂的NLP处理 concepts = [] # 简单关键词提取（实际应用中应该用更复杂的方法） concept_keywords = [ "吸引力", "价值", "框架", "需求感", "投资", "服从性", "筛选", "推拉", "冷读", "心锚", ] for concept in concept_keywords: if concept in text: concepts.append(concept) self.analysis["key_concepts"] = concepts def _extract_core_principles(self, text): """提取核心原则""" # 寻找原则性陈述 principle_indicators = [ "原则是", "核心是", "关键在于", "最重要的是", "本质是", "根本在于", ] principles = [] lines = text.split("。") for line in lines: for indicator in principle_indicators: if indicator in line: principles.append(line.strip()) break self.analysis["core_principles"] = principles[:5] # 取前5个 def _extract_practical_techniques(self, text): """提取实用技巧""" technique_indicators = ["方法", "技巧", "步骤", "操作", "做法", "策略", "战术"] techniques = [] lines = text.split("。") for line in lines: for indicator in technique_indicators: if indicator in line and len(line) < 100: # 避免太长的句子 techniques.append(line.strip()) break self.analysis["practical_techniques"] = techniques[:10] # 取前10个 def _extract_psychological_insights(self, text): """提取心理学洞察""" insight_indicators = [ "心理学", "心理", "潜意识", "认知", "情绪", "动机", "需求", "人性", ] insights = [] lines = text.split("。") for line in lines: for indicator in insight_indicators: if indicator in line: insights.append(line.strip()) break self.analysis["psychological_insights"] = insights[:8] def _identify_controversial_points(self, text): """识别争议点""" controversial_indicators = [ "脏", "强行", "操控", "套路", "欺骗", "利用", "不道德", "争议", ] points = [] lines = text.split("。") for line in lines: for indicator in controversial_indicators: if indicator in line: points.append(line.strip()) break self.analysis["controversial_points"] = points def _analyze_ethical_considerations(self, text): """分析伦理考量""" ethical_indicators = [ "尊重", "真诚", "诚实", "道德", "伦理", "责任", "伤害", "欺骗", ] considerations = [] lines = text.split("。") for line in lines: for indicator in ethical_indicators: if indicator in line: considerations.append(line.strip()) break self.analysis["ethical_considerations"] = considerations def _extract_key_quotes(self, text): """提取关键引述""" # 寻找可能的重要陈述 lines = text.split("。") quotes = [] for line in lines: line = line.strip() if len(line) > 20 and len(line) < 150: # 适中的长度 # 检查是否包含重要关键词 important_words = [ "爱", "感情", "关系", "心理", "方法", "技巧", "价值", "吸引", ] if any(word in line for word in important_words): quotes.append(line) self.analysis["key_quotes"] = quotes[:5] def _generate_summary(self, text): """生成总结""" # 简单的总结生成（实际应用中应该用LLM） summary = f"视频《{self.video_title}》主要探讨了" if self.analysis["key_concepts"]: summary += f"关于{', '.join(self.analysis['key_concepts'][:3])}等概念" if self.analysis["practical_techniques"]: summary += f"，提出了{len(self.analysis['practical_techniques'])}个实用技巧" if self.analysis["controversial_points"]: summary += f"，其中包含一些具有争议性的观点" if self.analysis["ethical_considerations"]: summary += f"，同时也涉及伦理考量" summary += "。" self.analysis["summary"] = summary def save_analysis(self, output_path): """保存分析结果""" with open(output_path, "w", encoding="utf-8") as f: json.dump(self.analysis, f, ensure_ascii=False, indent=2) print(f"分析结果已保存到: {output_path}") def print_analysis(self): """打印分析结果""" print("\n" + "=" * 60) print("视频内容分析报告") print("=" * 60) print(f"\n📺 视频标题: {self.analysis['title']}") print(f"📂 类别: {', '.join(self.analysis['category'])}") print(f"📝 总结: {self.analysis['summary']}") print(f"\n🔑 关键概念 ({len(self.analysis['key_concepts'])}个):") for concept in self.analysis["key_concepts"]: print(f" • {concept}") print(f"\n🎯 核心原则 ({len(self.analysis['core_principles'])}个):") for i, principle in enumerate(self.analysis["core_principles"], 1): print(f" {i}. {principle}") print(f"\n🛠️ 实用技巧 ({len(self.analysis['practical_techniques'])}个):") for i, technique in enumerate(self.analysis["practical_techniques"][:5], 1): print(f" {i}. {technique}") if len(self.analysis["practical_techniques"]) > 5: print(f" ... 还有{len(self.analysis['practical_techniques']) - 5}个技巧") print(f"\n🧠 心理学洞察 ({len(self.analysis['psychological_insights'])}个):") for i, insight in enumerate(self.analysis["psychological_insights"][:3], 1): print(f" {i}. {insight}") if self.analysis["controversial_points"]: print(f"\n⚠️ 争议点 ({len(self.analysis['controversial_points'])}个):") for i, point in enumerate(self.analysis["controversial_points"], 1): print(f" {i}. {point}") if self.analysis["ethical_considerations"]: print(f"\n⚖️ 伦理考量 ({len(self.analysis['ethical_considerations'])}个):") for i, consideration in enumerate( self.analysis["ethical_considerations"], 1 ): print(f" {i}. {consideration}") if self.analysis["key_quotes"]: print(f"\n💬 关键引述 ({len(self.analysis['key_quotes'])}个):") for i, quote in enumerate(self.analysis["key_quotes"], 1): print(f' {i}. "{quote}"') # 使用示例 if __name__ == "__main__": video_title = "一个很'脏'的方法，让你喜欢的女人强行爱上你！" analyzer = VideoContentAnalyzer(video_title) # 这里应该读取转录文本 # transcript = "转录文本内容..." # analysis = analyzer.analyze_transcript(transcript) # 保存分析结果 # analyzer.save_analysis("video_analysis.json") # analyzer.print_analysis() print("分析框架已创建，等待转录文本...")