Twitter API for Influencer Discovery

Filter on the numbers rather than on fame. Search for accounts posting about your topic, pull each profile, and keep the ones in your follower band, typically 1,000 to 50,000 for micro. Because profile reads are $0.0008 per call you can screen thousands of candidates for a few dollars, which is what makes the long tail workable at all; a per-seat tool that charges by the search tends to push you back toward the same well-known handles everyone else is pitching.

Sample rather than audit everything. Pull a few thousand followers, then compute what fraction have zero posts, a default avatar, or an account age clustered in a narrow window. Compare that against a creator you already trust in the same niche; the comparison is what makes the number mean something. Engagement is the second check: reach that does not move replies and reposts in proportion is the tell.

Automate the screening, keep the judgement manual. An API is very good at reducing ten thousand candidates to fifty on hard criteria: topic, follower band, posting cadence, engagement ratio, audience overlap with your existing customers. It is bad at deciding whether someone's voice suits your brand, and nobody should outsource that to a score. The useful split is machine for the funnel, human for the shortlist.

Source first, then vet. Sourcing means collecting candidates from category search results, name and handle search through GET /twitter/user/search, the accounts reposting popular posts in your niche through GET /twitter/tweet/retweeters, and a rival's follower list. Vetting means pulling each candidate's profile and recent timeline and computing engagement rate, reply ratio, posting consistency and topical fit. Sourcing 500 candidates costs around $0.06 and vetting them costs around $1.20 at a flat $0.0008 per call.

Judge it against the candidate set you are actually choosing between rather than an absolute benchmark, because rate falls predictably as follower count rises and category norms differ widely. As a working floor, below roughly 0.1 percent median engagement against followers, audience size has stopped meaning much. Rank your shortlist by rate rather than by reach, and expect the best rate in a set to belong to a smaller account.

Not directly. GET /twitter/user/search is X's People search, which matches display names and handles, not bio text. To use bios, source candidates first (topic authors, amplifiers, a rival's followers, or a name and handle search), then pull each profile with GET /twitter/user/info and filter on the bio yourself. Treat any bio match as a sourcing step rather than a result, since a bio is a self-description and says nothing about whether anyone engages with what that account posts.

No. TwitterAPIs authenticates with one Bearer token from signup, with no X developer application, no app review and no OAuth flow. Signup includes $0.50 in credit with no card on file, which is enough to source and vet several hundred candidates before you spend anything.

It gives you the raw signals to judge that yourself, which is the honest version of the answer. Pull a creator's followers and look at the distribution: account age, whether profiles have avatars and bios, follower-to-following ratios, and how many followers have never posted. A roster where most followers were created in the same window and never tweet is the classic bought-audience shape. We do not return a proprietary authenticity score, because that number would be our opinion rather than data.

For nearly every campaign, yes. Follower count is what an audience once was; engagement is what it currently does. A 10,000-follower account whose posts reliably draw hundreds of replies is usually worth more than a 500,000-follower account whose posts draw dozens. Both numbers come from the same endpoints here, so you can compute the ratio across a whole shortlist rather than trusting a media kit.

Yes, and it is the same endpoints pointed at a known list rather than at discovery. Poll each creator's timeline for posts matching your campaign hashtag or link, and pull engagement counts on a schedule to build the curve rather than a single end-of-campaign snapshot. At $0.0008 per call, tracking fifty creators hourly for a month is roughly $28.80.

Three signals, none of which needs a special product. Engagement rate is the first: an account with a large following and almost no engagement per post has an audience that is not present. Reply-to-like ratio is the second, because purchased engagement buys likes far more often than it buys conversation, so near-zero replies against high likes is a strong tell. The third is a follower sample: page one follower list, resolve a sample of those accounts, and look at creation dates and post counts. Ten profile calls, about $0.008, exposes an obviously bought audience.

Sourcing 500 candidates is about 70 calls, roughly $0.06. Vetting all 500 on profile plus two timeline pages each is about 1,500 calls, roughly $1.20. A follower-quality sample on the top 50 adds about 550 calls, near $0.44. Re-vetting a 200-creator roster monthly is about 600 calls, near $0.48. Compare that with per-seat influencer platforms, and the tradeoff is engineering time against a subscription.

Page GET /twitter/user/followers for both accounts and intersect on user id. High overlap means a campaign would mostly reach people who already follow you, which is a reason to negotiate differently rather than to walk away. This is the most expensive check on the page, because follower lists page at about 70 records on the first page and fewer after, so run it on a shortlist rather than on every candidate.

Usually because of the window and the maturity rule. Engagement accrues for days after a post, so a rate computed across posts of mixed ages understates the recent ones. Different tools also divide by different things, some by followers and some by estimated impressions, which produces numbers that are not comparable at all. Compute your own over a fixed window with a maturity cutoff, apply it identically to every candidate, and compare within your own set rather than against a figure from elsewhere.