manuscrape.org

What It Is

ManuScrape is an open-source research tool jointly developed by the University of Copenhagen’s MOD-Lab, Code Collective, and others. It is positioned for large-scale digital ethnography and online behavior research. Rather than being a traditional social media scraper, it emphasizes “Manual Scraping”: researchers use the desktop app to capture screenshots or scrolling screenshots of webpages or app screens, anonymize them, add observational notes and codes, and then submit them to a project for collaborative organization.

Core Features and Collaboration

Its core modules cover collection, anonymization, enrichment, collaboration, and export. For data collection, it supports standard screenshots and scrolling screenshots, and does not rely on platform APIs from Facebook, Instagram, Discord, Telegram, TikTok, WhatsApp, or similar services, giving it broad applicability. Anonymization tools are built into the app, allowing sensitive images or personally identifiable information to be masked locally. Projects can define custom coding fields and metadata, making it suitable for multiple researchers collecting data in a consistent structure. Project owners can invite collaborators by email; the documentation states that there is no limit on the number of collaborators, but it does not disclose fine-grained permission features such as roles or approval workflows.

Pricing, Deployment, and Developer Support

ManuScrape is released under the MIT open-source license and can be self-hosted on your own infrastructure. Its code and technical documentation are available on GitHub. The official public version hosted in Denmark at app.manuscrape.org is currently free, though storage or new features may be placed behind a paywall in the future. No specific pricing plans or payment details have been announced. The client supports Windows, Mac, and Linux; newer Mac versions may be less stable, while Linux users need to compile it themselves. Developer and user support is mainly provided through GitHub Issues and the Discord community. No formal commercial SLA or API documentation was found.

Data Security and Compliance

The product’s main value lies in its design around GDPR and research ethics: it supports removing personally identifiable information locally before data is uploaded to a server, and encourages teams to follow research ethics guidelines such as AoIR. Self-hosting and open-source code also help institutions conduct risk assessments and audit data processing. However, the official website makes clear that compliance and ethical responsibility remain with the researchers themselves; the tool does not automatically guarantee compliance.

Pros, Cons, and Best-Fit Users

Its strengths include open-source transparency, a low free-to-use barrier, self-hosting support, suitability for systematic multi-person collection of online observational data, and export compatibility with qualitative analysis software such as NVivo. Its limitations are that it currently does not provide in-app analysis, does not support video recording, video anonymization is still under development, and mobile research on some platforms requires phone screen mirroring. It is best suited to universities, research labs, student teams, and social science projects, and is less suitable for enterprise scenarios that require automated scraping, commercial customer service analytics, or built-in BI analysis.

Access from China and Alternatives

The available materials do not state whether it is accessible from mainland China, so this remains unknown. Since it supports self-hosting, Chinese teams concerned about network access, cross-border data transfer, or service stability may prefer deploying it on local servers. For downstream analysis, it can be used alongside tools such as NVivo, ATLAS.ti, Dedoose, or Excel. If a China-localized or fully local workflow is required, teams should evaluate local qualitative research data management and screenshot archiving solutions.