Twitter (X) Posts and Profiles Datasets

We provide two types of Twitter datasets: post dataset and profile dataset:

1. **Twitter - Posts Dataset**

**Description:** The "Twitter Posts Dataset" captures a wealth of information from tweets, including text, author details, posting date, media content, URLs, user interactions, and engagement metrics. This comprehensive dataset is a valuable resource for analyzing user behavior, content dynamics, and engagement patterns on Twitter. Researchers can study language trends and sentiment, while marketers can gain insights into content virality and audience preferences.

**Key Features:**

- Complete tweet details: text, author, date, media, URLs, and engagement metrics
- In-depth user interactions: quoted posts and tagged users
- External links and hashtags for comprehensive content analysis

**Popular Use Cases:**

- **User Behavior Analysis:** Understand how users interact with tweets, media, and hashtags.
- **Content Dynamics:** Analyze what makes content go viral and how different types of media impact engagement.
- **Sentiment Analysis:** Study language trends and sentiment shifts over time.
- **Engagement Strategies:** Optimize content strategies and post timing to maximize reach and impact.

**Related Subsets:**

- **Twitter Posts with more than 100k likes:** Analyze highly engaging posts for insights into effective content strategies.
- **Twitter Posts with Photos:** Understand the impact of visual content on engagement.

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2. **Twitter - Profiles Dataset**

**Description:** The "Twitter Profiles Dataset" captures extensive user-centric data, including names, bios, verification status, images, links, join dates, network sizes, locations, and activity metrics. This rich dataset is invaluable for analyzing user demographics, network structures, and account authenticity. Researchers and marketers can study self-presentation, identify influencers, and understand audience composition.

**Key Features:**

- Comprehensive profile details: names, bios, images, and links
- Verification status and activity metrics
- Network sizes and demographics

**Popular Use Cases:**

- **User Demographics:** Analyze user demographics and network structures.
- **Influencer Identification:** Identify influential users and potential collaborators.
- **Account Authenticity:** Study account verification and its impact on trust.

**Related Subsets:**

- **Twitter Profiles with more than 5M followers:** Study high-profile accounts for insights into engagement and influence.
- **Twitter Verified Profiles:** Analyze behavior and strategies of verified accounts to understand online popularity and credibility.

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Note: This is a sample

本次提供两类推特（Twitter）数据集：推文数据集与用户资料数据集：

1. 推特（Twitter）推文数据集
**数据集说明**：本推特推文数据集收录了推文的多维度信息，涵盖文本内容、作者详情、发布时间、媒体素材、统一资源定位符（URL）、用户交互数据与互动指标。该全面数据集是分析推特平台用户行为、内容动态与互动模式的宝贵资源：研究人员可借此开展语言趋势与情感倾向研究，营销人员则可从中获取内容传播性与受众偏好的洞见。
**核心特性**：
- 完整的推文详情：文本内容、作者信息、发布时间、媒体素材、URL与互动指标
- 深度用户交互数据：引用推文与被标记用户
- 外部链接与话题标签（Hashtag），支持全面的内容分析
**典型应用场景**：
- **用户行为分析**：探究用户与推文、媒体素材及话题标签的互动模式
- **内容动态分析**：解析驱动内容病毒式传播的核心要素，以及不同类型媒体对互动效果的影响
- **情感倾向分析**：研究语言趋势与情感倾向随时间的变化规律
- **互动策略优化**：优化内容策略与发布时机，以最大化覆盖范围与传播效果
**相关子数据集**：
- **点赞量超10万的推文数据集**：针对高互动量推文展开分析，挖掘高效内容策略的相关洞见
- **含图片的推文数据集**：探究视觉内容对互动效果的影响

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2. 推特（Twitter）用户资料数据集
**数据集说明**：本推特用户资料数据集收录了多维度的用户中心型数据，涵盖用户名、个人简介、认证状态、头像图片、个人链接、注册时间、社交网络规模、地理位置与活动指标。该优质数据集是分析用户人口统计学特征、社交网络结构与账号真实性的宝贵资源：研究人员与营销人员可借此开展用户自我呈现研究、识别影响力用户，并洞悉受众构成。
**核心特性**：
- 全面的用户资料详情：用户名、个人简介、头像图片与个人链接
- 认证状态与活动指标
- 社交网络规模与人口统计学特征
**典型应用场景**：
- **用户人口统计学分析**：分析用户人口统计学特征与社交网络结构
- **影响力用户识别**：识别具有影响力的用户与潜在合作对象
- **账号真实性研究**：探究账号认证机制及其对用户信任度的影响
**相关子数据集**：
- **粉丝量超500万的用户资料数据集**：针对高关注度账号展开分析，获取互动效果与影响力相关洞见
- **认证用户资料数据集**：分析认证账号的行为与运营策略，洞悉网络热度与公信力的形成逻辑

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注：本示例仅供参考

搜集汇总

背景与挑战

背景概述

该数据集包含Twitter的帖子数据和用户资料数据，帖子数据涵盖推文内容、作者信息和互动指标，适用于行为分析和情感研究；用户资料数据包含用户详细信息和社会网络规模，适用于人口统计和影响力分析。