Dear friends, I’m pleased to announce the latest (& greatest) release of Cactool. Cactool is a platform for easy human-coding of social media posts for content analysis. It was designed from the bottom-up for researchers who want to code social media or visual content, but don’t need the analytical tools (and cost) of other platforms – with easy import and exporting of data. The platform easily lets you contextually analyse a list of social media posts in their native form. Simply import a CSV that contains a list of social media posts (such as collected through scraping services); another to set your questions; and optionally set user logins, and the platform will do the rest – proving you with an easy-to-use human-coding platform. Set-up guides, worksheets, and documentation can be found on our website at: https://cactool.github.io/ Features: • No more coding via spreadsheets: Coding via your browser (tested working on Chrome, Firefox, Edge, & Safari) with posts visible as they would be on the social media platform. This allows your coders to evaluate social media content in their native format. • Simple Import and Export: Take your pre-existing social media URLs from software such as 4Cat, NodeXL, or API Scrapers and import them as a CSV list. When done, you can export your data via CSV to whatever analysis software you desire (such as SPSS/Excel). • Importing of image/text data: Have data from secondary source with no URLs? No Problem. • Manage Multiple Datasets: Want to split your project by source/themes? You can manage multiple concurrent datasets at the same time. • Built for collaboration: Cactool comes pre-packaged with user management; codes attributed are attributed to each coder for coder reliability calculation (such as ReCal). Multiple people can be coding at the same time without sharing documents. No need to worry about version control or splitting up data. • Code on the Go: Cactool is mobile friendly and can be accessed remotely (we recommend using a VPN to connect, see our tutorial for why). This provides researchers interested in social media content and spaciality new avenues of research. • Works with: Twitter; YouTube; TikTok; Instagram’ Mastodon (via OEmbed); Image Data (Photos/screenshots); Text Strings; & Some compatibility with other OEmbed platforms Cactool Development was funded by the University of Liverpool’s Research Development and Initiative Fund (RDIF). If you find Cactool useful, or have any comments or suggestions, please do get in touch! Best wishes, Liam Dr Liam McLoughlin (he/him) Lecturer in Communication & Media University of Liverpool, Department of Communication and Media Twitter: https://twitter.com/Leelum Website: https://Leelum.com Technology, Internet, & Policy Specialist Group Co-convenor https://twitter.com/psa_TIP Website: https://www.psa.ac.uk/specialist-groups/technology-internet-and-policy-tip