How Kylon + Social Scraper turns public social activity into research

Public social media is often the fastest place to see what customers, creators, competitors, and communities are actually discussing. It is also difficult to review at scale. Posts live across different platforms, video context gets lost in screenshots, and comment threads are easy to sample badly.

On Kylon, Social Scraper gives your agent access to public social media data from the major networks. No API key, no account, no configuration. You can ask a direct research question in your channel, and the agent can retrieve relevant public profiles, posts, videos, comments, search results, and available transcripts. It returns a focused answer instead of asking your team to log in, switch platforms, and copy links into a spreadsheet.

What you can do

Kylon's Social Scraper integration covers public data across four platforms:

• TikTok profiles and videos including public profile details, video listings, captions, engagement signals, comments, and available transcripts
• TikTok search and media research for public videos, creators, sounds, comments, and downloadable public media where supported
• Instagram profiles, posts, and reels including public post details, comments, and reel search
• X profiles, posts, and search for public account activity, posts, conversations, follower graph data, retweeters, and articles where available
• LinkedIn profiles and companies including public company pages, profiles, posts, and jobs
• Cross-platform comparisons that put several creators, brands, or conversations into one structured brief
• Comment and transcript analysis that identifies recurring questions, objections, phrases, and audience reactions

This is public-data research. It is not a tool for private messages, locked accounts, or unpublished analytics inside a social platform account.

How it actually works

Imagine a content lead is considering a TikTok campaign around small-business automation. They ask: “Find ten recent TikTok videos about automating admin work. Summarize the formats that get the most audience response, then group the comments by question or objection.”

The agent searches public TikTok results and reviews the relevant video metadata, captions, comments, and available transcripts. Rather than giving a raw feed, it can return a working brief: creator, post date, hook, video format, theme, engagement context, audience questions, and source. The team can then decide whether the opportunity is a tutorial series, a creator partnership, or a content angle to test.

The same approach works for competitor research. Ask: “Compare the last month of public LinkedIn posts from these five companies. What topics are they repeating, and which posts are drawing meaningful discussion?” The agent retrieves the public posts and produces a comparison by format, topic, tone, and visible response. If you need to verify a claim, ask for the original post links or request the relevant post text.

For customer research, you might ask: “Search X and Instagram for public posts mentioning a specific pain point. Separate product complaints from feature requests and general discussion.” The agent can search each platform and label the findings by theme. This makes it easier to distinguish a loud individual comment from a repeated pattern across independent users.

Common use cases

Social Scraper is most useful when the work depends on the words, examples, and reactions found in public social conversations.

Use platform-native analytics when you need private performance, account-level publishing tools, or audience data available only to the account owner. Use Social Scraper when the question is about what is publicly visible across accounts and networks.

Getting started

Give the agent a platform, a topic or list of accounts, and the decision you are trying to support. Useful requests include: “Review these creators,” “Find public comments about this problem,” or “Compare our competitors’ recent posts.”

Add a date range, language, location, or minimum activity level if those constraints matter. The agent will collect relevant public material, explain the pattern it sees, and preserve the source context for follow-up. There is no login to share and no separate social-listening workspace to manage.