AIGC漫剧题材选择与市场分析：热门赛道、受众画像与竞争格局

import json

class TopicAnalyzer:
    """AIGC漫剧题材分析与决策模型"""

    # 2026年题材数据库（评分1-10分）
    TOPICS_DB = {
        "废柴逆袭": {
            "market_size": 9.5,      # 市场规模（受众基数×播放天花板）
            "competition": 9.0,      # 竞争强度（越高越难突围）
            "production_difficulty": 5.0,  # 制作难度
            "monetization": 8.5,     # 变现潜力
            "avg_views": 85,         # 平均单集播放（万）
            "completion_rate": 0.68,  # 完播率
            "female_ratio": 0.70,    # 女性受众占比
            "monthly_new": 3000,     # 月新增作品数
            "platforms": ["抖音", "红果"],
            "key_hook": "身份反转+延迟满足"
        },
        "重生穿越": {
            "market_size": 8.5,
            "competition": 7.5,
            "production_difficulty": 5.5,
            "monetization": 8.0,
            "avg_views": 72,
            "completion_rate": 0.65,
            "female_ratio": 0.62,
            "monthly_new": 2000,
            "platforms": ["抖音", "红果", "B站"],
            "key_hook": "信息差降维打击"
        },
        "打脸虐渣": {
            "market_size": 8.0,
            "competition": 7.0,
            "production_difficulty": 4.5,
            "monetization": 7.5,
            "avg_views": 68,
            "completion_rate": 0.71,
            "female_ratio": 0.75,
            "monthly_new": 1800,
            "platforms": ["抖音", "红果"],
            "key_hook": "正义感释放+因果报应"
        },
        "甜宠霸总": {
            "market_size": 7.5,
            "competition": 6.5,
            "production_difficulty": 4.0,
            "monetization": 8.0,
            "avg_views": 55,
            "completion_rate": 0.72,
            "female_ratio": 0.85,
            "monthly_new": 1500,
            "platforms": ["抖音", "B站"],
            "key_hook": "被偏爱+甜蜜感"
        },
        "玄幻修仙": {
            "market_size": 7.0,
            "competition": 6.0,
            "production_difficulty": 8.0,
            "monetization": 7.0,
            "avg_views": 48,
            "completion_rate": 0.58,
            "female_ratio": 0.55,
            "monthly_new": 1200,
            "platforms": ["红果", "B站"],
            "key_hook": "升级突破+世界观探索"
        },
        "深宫宅斗": {
            "market_size": 5.0,
            "competition": 3.0,    # 蓝海：竞争低
            "production_difficulty": 7.5,
            "monetization": 6.5,
            "avg_views": 42,
            "completion_rate": 0.63,
            "female_ratio": 0.88,
            "monthly_new": 300,
            "platforms": ["B站", "抖音"],
            "key_hook": "权谋博弈+女性成长"
        },
        "虐恋BE": {
            "market_size": 4.0,
            "competition": 2.5,    # 蓝海
            "production_difficulty": 6.0,
            "monetization": 5.5,
            "avg_views": 35,
            "completion_rate": 0.55,
            "female_ratio": 0.80,
            "monthly_new": 200,
            "platforms": ["B站"],
            "key_hook": "刻骨铭心+情感宣泄"
        },
        "东方玄幻": {
            "market_size": 4.5,
            "competition": 3.5,    # 蓝海
            "production_difficulty": 8.5,
            "monetization": 6.0,
            "avg_views": 38,
            "completion_rate": 0.60,
            "female_ratio": 0.50,
            "monthly_new": 250,
            "platforms": ["B站", "红果"],
            "key_hook": "东方美学+文化底蕴"
        }
    }

    def __init__(self):
        self.weights = {
            "market_size": 0.30,
            "competition": 0.25,  # 注意：竞争越高分越低
            "production_difficulty": 0.15,  # 难度越高分越低
            "monetization": 0.30
        }

    def calc_topic_score(self, topic_name):
        """计算单个题材的综合得分"""
        t = self.TOPICS_DB.get(topic_name)
        if not t:
            return None

        # 竞争和难度是负向指标（越高越不利），取反
        competition_score = 10 - t["competition"]
        difficulty_score = 10 - t["production_difficulty"]

        score = (
            t["market_size"] * self.weights["market_size"] +
            competition_score * self.weights["competition"] +
            difficulty_score * self.weights["production_difficulty"] +
            t["monetization"] * self.weights["monetization"]
        )

        # 蓝海加成：月新增作品少于500的题材获得额外加分
        if t["monthly_new"] < 500:
            score += 0.5
            blue_ocean = True
        else:
            blue_ocean = False

        return {
            "topic": topic_name,
            "total_score": round(score, 2),
            "market_score": t["market_size"],
            "competition_score": round(competition_score, 1),
            "difficulty_score": round(difficulty_score, 1),
            "monetization_score": t["monetization"],
            "avg_views_wan": t["avg_views"],
            "completion_rate": f"{t['completion_rate']*100:.0f}%",
            "female_ratio": f"{t['female_ratio']*100:.0f}%",
            "monthly_new": t["monthly_new"],
            "blue_ocean": blue_ocean,
            "platforms": t["platforms"],
            "key_hook": t["key_hook"]
        }

    def rank_all_topics(self):
        """所有题材排名"""
        results = []
        for topic in self.TOPICS_DB:
            results.append(self.calc_topic_score(topic))
        results.sort(key=lambda x: x["total_score"], reverse=True)
        return results

    def recommend_for_creator(self, experience="new", platform="抖音",
                               target_gender="female", production_capacity="medium"):
        """
        根据创作者条件推荐题材
        experience: new(新手)/mid(中级)/pro(资深)
        platform: 抖音/红果/B站
        target_gender: female/male/mixed
        production_capacity: low/medium/high
        """
        ranked = self.rank_all_topics()
        recommendations = []

        for item in ranked:
            # 平台匹配
            if platform not in item["platforms"]:
                continue
            # 性别匹配
            if target_gender == "female" and int(item["female_ratio"].rstrip("%")) < 60:
                continue
            if target_gender == "male" and int(item["female_ratio"].rstrip("%")) > 50:
                continue
            # 制作能力匹配
            if production_capacity == "low" and item["difficulty_score"] < 3:
                continue
            # 新手优先热门赛道（有参考模板）
            if experience == "new" and not item["blue_ocean"]:
                item["recommend_reason"] = "热门赛道，有成熟成功模板可参考"
            elif experience == "pro" and item["blue_ocean"]:
                item["recommend_reason"] = "蓝海赛道，竞争低，适合建立差异化壁垒"
            else:
                item["recommend_reason"] = "综合评分优秀"

            recommendations.append(item)

        return recommendations[:3]  # 返回Top 3推荐

    def market_overview(self):
        """市场总览"""
        total_monthly_new = sum(t["monthly_new"]
                                for t in self.TOPICS_DB.values())
        top3_share = sum(t["monthly_new"] for t in list(self.TOPICS_DB.values())[:3])
        blue_ocean_count = sum(1 for t in self.TOPICS_DB.values()
                              if t["monthly_new"] < 500)

        return {
            "tracked_topics": len(self.TOPICS_DB),
            "total_monthly_new_works": total_monthly_new,
            "top3_market_share": f"{top3_share/total_monthly_new*100:.1f}%",
            "blue_ocean_topics": blue_ocean_count,
            "avg_completion_rate": f"{sum(t['completion_rate'] for t in self.TOPICS_DB.values())/len(self.TOPICS_DB)*100:.0f}%",
            "female_audience_avg": f"{sum(t['female_ratio'] for t in self.TOPICS_DB.values())/len(self.TOPICS_DB)*100:.0f}%"
        }


# ===== 使用示例 =====
analyzer = TopicAnalyzer()

# 市场总览
print("=== AIGC漫剧题材市场总览 ===")
overview = analyzer.market_overview()
for k, v in overview.items():
    print(f"  {k}: {v}")

# 题材排名
print("\n=== 题材综合评分排名 ===")
ranking = analyzer.rank_all_topics()
for i, item in enumerate(ranking, 1):
    ocean = " [蓝海]" if item["blue_ocean"] else ""
    print(f"  {i}. {item['topic']}: {item['total_score']}分{ocean}"
          f" | 均播{item['avg_views_wan']}万 | 完播{item['completion_rate']}"
          f" | 月新增{item['monthly_new']}")

# 个性化推荐
print("\n=== 个性化推荐（新手/抖音/女性受众/中等产能）===")
recs = analyzer.recommend_for_creator(
    experience="new", platform="抖音",
    target_gender="female", production_capacity="medium"
)
for rec in recs:
    print(f"  {rec['topic']} ({rec['total_score']}分)")
    print(f"    理由: {rec['recommend_reason']}")
    print(f"    核心钩子: {rec['key_hook']}")
    print(f"    平台: {', '.join(rec['platforms'])}")

# 蓝海推荐
print("\n=== 蓝海题材推荐（资深创作者）===")
recs_pro = analyzer.recommend_for_creator(
    experience="pro", platform="B站",
    target_gender="female", production_capacity="high"
)
for rec in recs_pro:
    print(f"  {rec['topic']} ({rec['total_score']}分) - {rec['recommend_reason']}")

建议新手从热门题材切入。原因有三：第一，热门题材有大量成功案例可参考，学习和模仿成本最低；第二，热门题材的受众基数大，即使作品质量一般也能获得一定的基础流量；第三，热门题材的叙事套路成熟，新手容易掌握节奏。蓝海题材虽然竞争低，但缺乏参考模板，对创作者的原创能力要求更高，适合有一定经验后再尝试。简言之：新手靠"模仿"起步，老手靠"差异化"突围。

三种有效的差异化策略：第一，"题材融合"——将两个热门题材的元素组合（如"废柴逆袭+悬疑推理"），产生新鲜感；第二，"视角创新"——在同一题材中切换叙事视角（如打脸虐渣从"受害者视角"转为"反派视角"）；第三，"人设突破"——打破题材的典型角色设定（如甜宠霸总中女主是强势CEO、男主是温柔型）。关键是在保持题材核心爽感的前提下，找到一个让观众"意料之外又情理之中"的创新点。

各平台有不同的题材偏好和受众画像。抖音以快节奏爽剧为主，推荐逆袭/种田/都市脑洞，受众年龄偏年轻（18-30岁），需要前3秒强钩子；红果短剧偏重玄幻修仙/都市穿越，受众消费能力强，适合做付费转化；B站用户文化层次较高，适合高品质连载和多元题材，对画面质量和剧情深度要求高。建议根据你的制作能力和目标受众选择主攻平台，同一作品在不同平台的表现可能差异巨大。

会变化，且变化速度在加快。AIGC漫剧的题材热度周期通常为3-6个月——一个新题材从兴起到饱和大约需要3个月，从饱和到衰退约需3个月。提前布局的方法：第一，关注短剧（真人）赛道的热门题材，AIGC漫剧通常滞后真人短剧1-2个月跟风；第二，观察各平台的热搜榜和上升榜，发现新题材苗头；第三，关注网文平台（番茄、七猫）的新书排行榜，网文热度往往领先漫剧2-3个月。在题材热度上升期入场，是性价比最高的时机。