Social Media Data Scraping Services

No. We collect only what is publicly visible without authentication. We do not create accounts, use credential pools, buy access to authenticated sessions, or scrape logged-in views.

Any vendor offering private-account data or authenticated-view depth is describing collection that breaches platform terms and, in some jurisdictions, more than that. The risk of using such data does not stay with the vendor — it attaches to the party processing it, which would be you.

Coverage is strongest where official APIs exist and are accessible: YouTube via the Data API, Reddit via its API, Twitch, and X within its API tiers. Public-page collection works reasonably for Instagram public profiles, TikTok public videos, Facebook Pages, Pinterest and public LinkedIn company posts.

Depth varies considerably even within a platform — public engagement counts may be available while audience demographics are not. We provide a field-by-field matrix during scoping so you see exactly what is obtainable per platform before you commit, rather than discovering the gaps in month two.

Not far, honestly, and this is where claims should be scrutinised hardest. Platforms restrict historical access aggressively. Where an official API permits historical queries we can retrieve within those limits. Where we already collect a platform for other clients, our own archive provides some depth.

Deep multi-year social history across major platforms is not something we can supply, and we would question how any vendor obtained it. For most social use cases the practical answer is that your series starts when collection starts — which is a strong argument for beginning earlier than you think you need to.

We surface signals rather than issue verdicts. Engagement spikes inconsistent with follower growth, follower-growth curves showing implausible step changes, comment patterns with low linguistic diversity, and engagement-rate outliers versus platform and tier norms are all reported as flags with supporting numbers.

We stop short of declaring an account fraudulent, because that determination requires data platforms don't expose publicly. What we provide is enough evidence for your team to ask better questions before signing a rate card — which is usually what's actually needed.

We check each post for disclosure in several forms: hashtags such as #ad, #sponsored or #gifted, platform-native paid-partnership labels, and in-caption disclosure language. We record whether a disclosure is present, which form it takes, and where it appears — prominence matters to regulators, since a disclosure buried after a 'more' truncation is often treated as inadequate.

Every check is archived with a timestamp and a screenshot, so you hold evidence of what was published when. Alerting can fire within hours of a non-compliant post rather than surfacing in a quarterly review.

We extract publicly visible comment text with engagement metrics, and we deliberately avoid building profiles of individual commenters. Comment data is delivered in aggregate and thematic form — sentiment distribution, recurring themes, extracted text — rather than as a database keyed to individuals.

Commenter handles can be excluded entirely on request, and for most research use cases we recommend that: the analytical value is in the language and sentiment, not in who said it. If your use case genuinely requires commenter-level data, that needs a specific discussion about basis and purpose before we agree to it.

We notify you immediately, explain which fields are affected, and mark them with a platform_restricted null reason so your pipeline can detect the change programmatically rather than silently ingesting empty columns.

Where an alternative public route exists within terms, we implement it and tell you how the methodology changed — because a methodology change mid-series affects comparability, and you need to know that. Where no compliant alternative exists, we say so and adjust your subscription rather than continuing to bill for a field we can no longer deliver.

Technically we can deliver clean paired text and media with engagement labels and full provenance. Whether you may train on it depends on platform terms, the rights of the original creators, and your jurisdiction — and the answer is often more restrictive than for other data types.

We document collection method and source per record so your legal team can assess it. We will not assert that you have training rights over user-generated content, because in most cases neither we nor the platform holds those rights to grant. If training is your purpose, raise it during scoping: the source selection and the conversation both change.

We quote every social media data engagement individually, because a real number depends on scope: source count, record volume, refresh frequency and delivery method. Anyone quoting you a price before understanding those four things is guessing.

Platform mix drives cost more than volume, because platforms differ enormously in what they permit and how expensive lawful access is.

The process is short: one scoping call, a free pilot on your own sources within 48 hours, then a fixed monthly quote. No per-request metering, no overage billing, and field or source additions are handled inside the retainer rather than re-quoted. Request a quote.