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Abstract We present the first results from Citizen ASAS-SN, a citizen science project for the All-Sky Automated Survey for Supernovae (ASAS-SN) hosted on the Zooniverse platform. Citizen ASAS-SN utilizes the newer, deeper, higher cadence ASAS-SN g -band data and tasks volunteers to classify periodic variable star candidates based on their phased light curves. We started from 40,640 new variable candidates from an input list of ∼7.4 million stars with δ < −60° and the volunteers identified 10,420 new discoveries which they classified as 4234 pulsating variables, 3132 rotational variables, 2923 eclipsing binaries, and 131 variables flagged as Unknown. They classified known variable stars with an accuracy of 89% for pulsating variables, 81% for eclipsing binaries, and 49% for rotational variables. We examine user performance, agreement between users, and compare the citizen science classifications with our machine learning classifier updated for the g -band light curves. In general, user activity correlates with higher classification accuracy and higher user agreement. We used the user’s “Junk” classifications to develop an effective machine learning classifier to separate real from false variables, and there is a clear path for using this “Junk” training set to significantly improve our primary machine learning classifier. We also illustrate the value of Citizen ASAS-SN for identifying unusual variables with several examples. 

We catalogue the 443 bright supernovae (SNe) discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) in 2018−2020 along with the 519 SNe recovered by ASAS-SN and 516 additional mpeak ≤ 18 mag SNe missed by ASAS-SN. Our statistical analysis focuses primarily on the 984 SNe discovered or recovered in ASAS-SN g-band observations. The complete sample of 2427 ASAS-SN SNe includes earlier V-band samples and unrecovered SNe. For each SN, we identify the host galaxy, its UV to mid-IR photometry, and the SN’s offset from the centre of the host. Updated peak magnitudes, redshifts, spectral classifications, and host galaxy identifications supersede earlier results. With the increase of the limiting magnitude to g ≤ 18 mag, the ASAS-SN sample is nearly complete up to mpeak = 16.7 mag and is 90 per cent complete for mpeak ≤ 17.0 mag. This is an increase from the V-band sample, where it was roughly complete up to mpeak = 16.2 mag and 70 per cent complete for mpeak ≤ 17.0 mag.