K-Food Trend Watch: What the Internet Is Eating

**K-Food Trend Watch** tracks the ongoing cultural rise of Korean food and flavors across the social web. The dataset captures a rolling 30-day window of public conversations — posts, comments, threads, and short-form video activity — spanning online forums, community boards, short-form video platforms, and consumer review sites. Every refresh brings a current, unfiltered view of what people are actually saying about Korean cuisine, ingredients, and food culture. **What's Included:** **Content & Engagement** — Posts, comments, and videos tied to Korean food topics, with full text, publication timestamps, platform source, and engagement metrics (views, likes, comments, shares) where available. Content is tagged with hashtags and topic labels for filtering and trend analysis. **Conversation Context** — Parent-child thread relationships are preserved, enabling reconstruction of full conversation threads from root post to final reply. This structure surfaces the *signal inside the thread* — not just what was posted, but how audiences responded, debated, and built on each other's ideas. **Author & Creator Profiles** — Creator and author metadata including display names, platform affiliation, follower counts, post history, and engagement performance. Supports influencer identification and community voice analysis. **AI-Ready Data** — Content is pre-chunked for LLM and embedding workflows, with a Cortex Search Service attached for semantic retrieval. A Snowflake Cortex Analyst Semantic View is included, enabling natural language queries against the full dataset without writing SQL. **Ask your agent:** - *What Korean food topics are generating the most conversation this week?* - *Which creators are driving the highest engagement around K-Food content?* - *What does the thread activity around tteokbokki look like — what are people actually saying?* This dataset is designed for brand teams, category managers, trend researchers, and cultural strategists tracking the momentum of Korean food and flavors in Western consumer culture. It supports flavor innovation research, cultural trend forecasting, creator and influencer discovery, and consumer sentiment analysis across the social web.

原始信息汇总

数据集名称

K-Food Trend Watch: What the Internet Is Eating

数据集提供方

Socialgist

定价类型

免费（Unlimited Access）

数据集概述

该数据集追踪韩国美食在全球社交媒体上的实时趋势与文化热度。它捕捉社交媒体上关于韩国美食的公开对话，覆盖在线论坛、社区留言板、短视频平台和消费者评论网站，数据窗口为滚动30天。

核心内容

• 内容与互动：包含与韩国美食主题相关的帖子、评论和视频，提供完整文本、发布时间、平台来源以及互动指标（如浏览量、点赞、评论、分享）。内容已打上话题标签和主题标签，便于过滤和趋势分析。
• 对话上下文：保留父子帖子的完整对话线索（从根帖子到最终回复），支持还原完整讨论线程，揭示用户如何回应、辩论和相互补充。
• 作者与创作者画像：包含创作者和作者的元数据，如显示名称、平台归属、粉丝数、发帖历史和互动表现，支持影响者识别和社区声音分析。
• AI就绪数据：内容已预先分块，适用于大语言模型（LLM）和嵌入工作流。附有Cortex Search Service用于语义检索，并包含Snowflake Cortex Analyst语义视图，支持用自然语言查询整个数据集。

业务应用场景

• 对话情报：通过保留论坛、社区、短视频及评论网站的完整对话线程，分析韩国美食趋势如何在网络文化中传播、哪些声音具有影响力、哪些讨论最活跃。
• 消费者洞察：了解消费者对韩国美食的真实看法，识别哪些菜品或食材正在破圈，以及美食文化如何演变，支持CPG品牌和零售商的产品创新、开发和市场进入决策。
• 情感分析：追踪消费者对韩国美食、风味和食材态度的变化，30天滚动窗口可实时捕捉新兴热情、摩擦点和文化瞬间。

数据字典

• 核心表：CONTENT_ITEMS
• 关键字段：OBJECT_ID、PLATFORM、ENTITY_TYPE、PUBLISHED_AT、AUTHOR_ID、PARENT_OBJECT_ID、ROOT_OBJECT_ID、URL、CHANNEL_ID、CONTENT_TEXT、TAGS等。
• 每条记录代表一个社交媒体平台上的帖子。大多数其他表可通过OBJECT_ID与此表关联。

使用示例

• 查询数据集平台来源的构成，示例SQL按平台和实体类型统计帖子数量。

数据刷新与时间覆盖

• 刷新频率：每日更新
• 时间覆盖：最近30天 / 基于事件

数据获取方式

• 交付方式：Secure Share

其他信息

• 数据已集成Cortex AI能力（Cortex AI Ready）。
• 适用类别：市场营销、情感分析。