Which Reddit threads, YouTube videos, and LinkedIn pages appear in your AI answers?

To find which Reddit threads, YouTube videos and LinkedIn pages appear in your AI answers, list the social links your monitored prompts cited over a fixed window, then sort each page by what it asks of you. Some are content opportunities (a question you could answer well in your own channels). Some are reputation questions (what a page says about you or a rival). Some need nothing. Citation counts tell you what was linked, not that a page caused the answer, and they are never a licence to post in a community.

In short

• A social source is a cited link on a recognised network such as Reddit, YouTube or LinkedIn. It is an observation of one answer, not proof of influence.
• Identity comes from the URL alone. A YouTube watch page or a LinkedIn Pulse article counts for its network but not for any account, so read those pages by hand.
• Sort every cited page into opportunity, reputation question, or no action, and write down the evidence before choosing.
• Read the thread or watch the video before you summarise it. A saved link does not tell you what the page says.
• Frequency does not entitle you to post. Community rules, disclosure and usefulness come first.

What counts as a social source in an AI answer?

A social source is a citation whose URL sits on a recognised social, community, video, publishing, developer, review or podcast network. A citation is a link an AI engine places in its answer as the source for a claim. DiscoveredBy's Social sources screen groups them into families: community (Reddit, Quora, Hacker News), video (YouTube, TikTok, Vimeo), social (LinkedIn, X, Facebook and others), publishing (Medium, Substack), developer (GitHub), reviews and podcasts.

Identity comes only from the cited URL. No social page is fetched and no model reads it, so nothing on that screen knows what a thread or video actually says. It matches real network hosts, so a lookalike domain that merely contains the word "reddit" is not counted.

A network can be recognised without an account being identified. A YouTube watch page, a LinkedIn Pulse article, a Quora question page and a shortened redd.it link count toward their network but have no account attached. They appear in the network row and in the Not identifiable tile, never in the accounts table. For a video-heavy category, that can be a large share of what you most need to read.

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How do you read the Social sources screen?

Read it at network level first, account level second, then open the individual URLs. The screen shows, for a period you choose (7, 28 or 90 days, defaulting to 28 and ending yesterday), the number of outputs (completed runs in scope), the prompts that ran, and the social share of citations: the share of all recorded citations that parsed as social. It is a share of citations, not of answers.

The Networks table gives each network's citations, its cited outputs (distinct completed runs that cited any URL on it), an output rate, the change against the previous equal-length period in percentage points, and how many prompts it reached. The Accounts table adds reach (how many prompts cited the account, shown as "3 of 14"), consistency (the mean share of runs that cited it across those prompts) and influence (reach multiplied by consistency).

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Treat the word "influence" carefully. It describes what was cited, not that an account caused an answer. An account with fewer than 30 observed runs is marked provisional, so do not build a plan on it. Select Details on an account to see its cited URLs, the engines that cited them and up to three example prompts.

Two behaviours matter for interpretation:

• If an engine was not measured in both periods, every change on the page is withheld, and you should choose an engine to compare.
• At most 5,000 distinct social URLs are parsed per request. Past that, counts are lower bounds and rates and changes are unreliable, so shorten the window.

Also filter by engine. Engines record citations differently, and for Claude every page its search returned is stored as a citation (see Retrieved vs cited and Engines). A Reddit link recorded that way may mean the engine's search returned the page, not that the answer credited it.

Whose accounts are these?

Each social account is labelled yours, a tracked competitor's, or unlabelled, by comparing its network and account key with two lists. Your own profiles are added in project settings by the project owner; a competitor's profiles are added from that competitor's own page (see Competitors). Only an active competitor's profiles label anything. An unlabelled row offers Assign so you can attach it to yourself or a competitor.

Every social citation lands in exactly one bucket: Yours, Competitor, Unlabelled or Not identifiable. A label is only as accurate as the profile a team member entered; nothing verifies that a saved profile really belongs to the account it names.

The screen also lists prompts where a competitor's social account was cited and none of yours was. That list is a useful starting point for opportunity review, capped at 50 rows.

How do you turn a list of links into decisions?

Give every cited page exactly one of three outcomes, and write down the evidence that supports it. The outcomes are opportunity, reputation question, or no action. Sorting by page content, not by network, keeps the review honest, because a Reddit thread can be any of the three.

First, open each page. The Source types screen helps you organise them: it suggests that Reddit thread paths are user-generated discussion and YouTube watch and shorts paths are social video. Those are URL-based rule suggestions, not verified classifications, and you can override the category for a page or a whole domain, and the page format for a single page. The screen examines at most 500 pages, so category counts describe that limited set when the cap applies.

Getting the URLs is part of the job. Details on an account lists its cited URLs, but account-less pages (a YouTube watch page, a Pulse article) have no account row to open. For those, use the Citations page, whose Sources tab groups cited URLs, and scan for the network's address. That page is built from the newest 500 citations in the window, so a busy project may need a shorter window.

Then use this table to sort.

Reddit: threads are conversations

For a cited Reddit thread, read the question and the top replies. Ask whether the thread is a genuine buyer question, who answered it, and whether the answers are accurate and current. You cannot edit a thread someone else started, so the choices are to answer honestly where the rules allow it, improve your own pages so the question has a clear answer elsewhere, or leave it.

YouTube: read the video, not the title

A cited video may be a review, a tutorial or a competitor's walkthrough. Watch it, or read its transcript, before writing down what it claims. A saved URL alone does not establish what the video says. For a fuller workflow on cited videos, see Turn cited video questions into an editorial research brief.

LinkedIn: separate company pages from individual voices

A LinkedIn citation might be your company page, a competitor's, an employee's article, or a Pulse piece with no identifiable account. Your own profiles are the easiest to act on, since they are yours to update. For third-party posts, treat them as one person's public view.

The source-review worksheet

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Copy one row per cited page. Fill in the evidence columns before the decision columns.

SOURCE REVIEW WORKSHEET
Project: ______  Window: ____ to ____  Engine filter: ______
Reviewer: ______  Review date: ______

Row | Network | Page URL | Label (yours / competitor / unlabelled / not identifiable)
    | Account (or "none") | Prompts that cited it (list up to 3)
    | Engines that cited it | Cited outputs | Account provisional? (under 30 observed runs: Y/N/no account)

Read the page:
    | What the page actually says (2 sentences, in your words)
    | Date of the page or last edit | Author or account type (person / brand / unknown)
    | Is it accurate about us and the category? (Y / N / Partly / Unverified)

Decision:
    | Outcome: Opportunity / Reputation question / No action
    | Evidence for the outcome (one line)
    | Owner | Next action | Due date
    | Community rules checked? (Y / N / Not applicable)
    | Would we disclose our affiliation? (Y / N)
    | Claim strength: Observed / Likely / Hypothesis

Follow-up:
    | Re-check date | What we saw on re-check | Closed? (Y / N)

Two habits keep the sheet useful. Write "Unverified" rather than guessing when you have not read the page. And use the claim-strength column: "Observed" means it appeared in a saved answer, "Hypothesis" means you think acting on it could help.

Worked example: Quillstone reviews a month of social citations

Illustrative example: Quillstone and its competitors are fictional, and the numbers are made up to show the method.

Quillstone sells document-review software to legal and compliance teams. Its competitors include Brieflane and Clausewise. Over a 28-day window, 100 completed outputs ran, and 200 citations were recorded, of which 25 parsed as social: 12.5% of citations.

The label split across the 25 social citations: 4 Yours, 7 Competitor, 8 Unlabelled, 6 Not identifiable (4 + 7 + 8 + 6 = 25). The four Yours are all Quillstone's LinkedIn company page. The 7 competitor citations are 3 that name a Brieflane YouTube channel and 4 from a subreddit that Quillstone assigned to Clausewise. The 8 unlabelled citations are all Reddit. The 6 not identifiable are 5 YouTube watch pages and 1 LinkedIn Pulse article.

The team reviews the pages, not just the numbers.

1. Unlabelled Reddit citations, 8. A reviewer reads the threads and finds three are genuine questions about redlining contracts for audit. Outcome: opportunity. The next action is a brief for a plain-language guide on Quillstone's own site, with a decision on whether a named team member can help in the thread if the subreddit's rules allow it.
2. Five YouTube watch pages, not identifiable. The reviewer watches all five. Two are competitor demos; one compares three tools and gets a Quillstone feature wrong. Outcome for that one: reputation question. Check the claim against approved product information, then decide whether to comment, publish a clearer page, or record it and move on.
3. Brieflane's YouTube channel, 3 citations, competitor-labelled. The team notes on which prompts it is cited and that Quillstone has no video on those topics. The competitor-only prompts list on Social sources shows one such prompt. Outcome: opportunity, hypothesis strength. They do not conclude that the videos caused Brieflane to be recommended.
4. LinkedIn Pulse article, 1 citation. The article is from an independent author and accurate. Outcome: no action, recorded.

After a re-check next month, Quillstone can compare a window of the same length. If the count of Reddit citations changes, it still cannot say the cause was a new guide.

What this review cannot tell you

• Cause. A social link in an answer does not show that it shaped the recommendation. Stated reasons, mentions and citations are observations of one answer.
• What a page says. The screen never fetches a social page or calls a model, so the text of a thread, video or post is yours to read.
• Which accounts are missing. Account-less URLs are counted for the network only. The Not identifiable tile can hide the pages you most need to open.
• Full coverage. Bounds apply: 5,000 parsed URLs for the social screen and 500 pages for Source types. When they bite, counts describe part of the set.
• Permission. Frequency does not make a community welcoming. The community decides what is acceptable.

Common mistakes

• Treating the influence column as proof that an account moved an answer.
• Summarising a video or thread from its title or link.
• Comparing periods without choosing an engine when engines changed between them. The page withholds every change in that case, and the fix is to pick one engine.
• Assigning an account to a competitor without checking who runs it; a label is only as accurate as the profile entered.
• Replying with marketing copy. It can harm the reputation you are trying to protect.

Frequently asked questions

Do AI engines really cite Reddit, YouTube and LinkedIn?

Your own data answers this, not a general claim. The Social sources screen lists the social links your engines cited for your prompts, so check whether any appear and on which prompts. What appears varies by engine, prompt and time, so read it as a description of your monitored set only.

Can I see what a cited YouTube video or Reddit thread says inside DiscoveredBy?

No. The Social sources screen identifies networks and accounts from the URL alone and never fetches the page. Open the link and read or watch it yourself, then record your notes in the worksheet.

Should I post in a Reddit thread that AI keeps citing?

Only if you would be welcome without the citation. Check the community's rules, disclose who you are, and add something useful. If you cannot do that, improve your own pages or leave it alone.

How is a social source different from a review or an editorial source?

They come from two different screens. Social sources groups cited URLs by network family (review sites such as Trustpilot and G2 are a family there, alongside community, video and others), from the URL alone. Source types is where you label a cited page with a source category (such as Editorial or User-generated) and a page format, and those labels are your own or rule suggestions. A page can appear in both views. For review-site evidence see Review-site citations: separate product evidence from customer opinion.

How many citations do I need before an account is worth acting on?

The screen counts runs rather than citations: an account with fewer than 30 observed runs is marked provisional, so treat a smaller sample as a lead to investigate. There is no number at which action is guaranteed to help, which is why the worksheet uses a claim-strength column.

What if the social page is wrong about my product?

Check it against your approved product facts first, then choose a proportionate response, from clarifying your own docs to a public correction where the platform permits it. If the page is a third-party article rather than a social post, Find third-party pages worth approaching from your AI citation data covers that route.

Next step

Open the Social sources screen for a 28-day window, filter to one engine, and fill the worksheet for ten cited pages (start with the accounts that reach the most prompts), reading each before you decide. Availability depends on your plan; see plans and limits, and the Sources feature page for the wider picture. To go beyond one review, Which kinds of sources appear across different buying questions? is a study protocol on source types. Start with DiscoveredBy to list the social sources your own prompts cite.