These are the 50 largest of the more than 1,000 historical Twitter datasets available via DiscoverText for teaching and research. All software and data is free for academic researchers. For authenticity and compliance, Tweets are displayed using the Twitter display. Deleted Tweets and suspended accounts are not displayed. There is a significant amount of understudied historical data. Signing up does not get you access to all 300,000,000 Tweets in 1,200 projects. It does start a process where we can talk about your research or teaching needs and the best way to meet them using the collaborative architecture of DiscoverText. Sharing web-based access to a single copy of the data, rather than making copies for every user, is another one of the measures that makes this ToS compliant. We have user-friendly methods for sampling to make the very large sets more manageable and focused, including search, filtering, clustering, duplicate detection, crowdsource annotation, and machine-learning. For example, if you need to separate Tweets about human migration from Tweets about non-human migration, that data cleaning method using humans and machines is in our wheelhouse. If you want to measure and report inter-rater reliability, we started doing that in 2007 at Pitt and it is a core feature. If you want to adjudicate annotator disagreements to create gold standard training sets, while improving and measuring annotator awareness, it is the most powerful (least used) piece of the research platform. DiscoverText is an NSF-funded scientific instrument. https://tinyurl.com/dtarchives Topics in the 50 largest include: COVID, Trump, Brexit, Biden, Bots, Suicide, Policing, Elections, Racism, and Gettr. Date ranges in the 50 largest: 2017-2022 Archive size in the 50 largest: 1.2 million - 11.5 million Topics in the most recent smaller 2023 collections (10,000 - 1,200,000) include: BLM, "Pureblood" ideology, #voice (Australia), digital soldiers, LGBTQ+ advocacy, vaping, the Lahaina fire, QAnon's return, anti-Semitism, AmericaFirst, and a range of other events or trends where we suspect Tweets, whether we like it or not, seem to play an outsized role in the public perception of events. If you are studying a current event, at least for now, we can still create a custom dataset from the last 12 months of Twitter. This may not be an option in the future, but it is one now. Free sign up: https://app.discovertext.com/Home/SignupContactTrialView Free consultation: https://calendly.com/discovertext Scholarly mentions (DT literature review in a box): https://discovertext.com/mentions/ Stu -- Dr. Stuart W. Shulman Founder and CEO, Texifter Editor Emeritus, *Journal of Information Technology & Politics*