Twitter Posts Scraper — Twitter (X) | Lagic

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Overview

Extract comprehensive data from individual X (formerly Twitter) posts, including the full post text, author's profile details, and engagement metrics like likes, reposts, replies, and views, to power your social media analysis or content strategy.

This tool provides a deep dive into specific public X posts. By simply providing the URL of a post, you gain access to a wealth of structured data, moving beyond surface-level observation to granular analysis. ### What You Get From Each Post For every post URL you submit, you'll receive its complete description (the tweet's text), the exact date and timestamp it was published, and unique identifiers for both the post and its author. You'll also see key engagement figures: how many likes, reposts (formerly retweets), replies, quotes, and even bookmarks the post has accumulated. Critically, the tool also captures the total view count, a metric often hard to obtain reliably. ### Author Profile Details Beyond the post itself, this scraper delivers crucial information about the post's author. You'll get their display name and username, a link to their profile image, their unique user ID, and their full biography if available. The tool also indicates if the account is verified and, if so, the type of verification. Further context comes from the author's follower and following counts, and their total number of posts. ### Media and Related Posts If the post includes images or videos, their links are provided. For posts that are replies or quote another post, the tool attempts to capture details about the parent post or the quoted post, offering a fuller conversational context. This is invaluable for understanding the lineage and impact of discussions on X. ### Ideal for Data-Driven Decisions Whether you're monitoring brand mentions, analyzing competitor content, tracking viral trends, or conducting academic research, having this level of detail for individual posts is essential. It enables sentiment analysis, performance benchmarking, and content effectiveness studies that are grounded in hard data.