From: Real-time spatio-temporal event detection on geotagged social media
Event time | C | Area | Top hashtag/mentions |
---|---|---|---|
Events using smoothing method with \(\tau _1 = 0.00125\) | |||
 -S 01-18 10:10 -D 50 | 27 | 6.969 | #funk, @choiproductions, #nofilterwtf, @jeffreymayfield, #saxophone |
 -S 01-21 07:50 -D 70 | 20 | 0.435 | #gostars, @mcg, #mcg, #bbl06, #melbourne |
 -S 01-22 02:10 -D 70 | 18 | 0.109 | #50th |
 -S 01-22 08:20 -D 60 | 15 | 0.109 |  |
 -S 01-29 12:10 -D 60 | 72 | 1.741 | #ausopen, #australianopen, #federer, #rogerfederer, #champion |
 -S 01-29 12:10 -D 70 | 73 | 0.109 | #ausopen, #australianopen, #federer, #champion, #rogerfederer |
Events using smoothing method with \(\tau _1 = 0.000625\) | |||
 -S 01-21 08:10 -D 50 | 14 | 0.435 | #gostars, #mcg, @mcg, #bbl06, #melbourne |
 -S 01-29 12:10 -D 70 | 73 | 0.109 | #ausopen, #australianopen, #federer, #champion, #rogerfederer |
Events using Poisson signal with \(\tau _1 = 0.0003125\) | |||
 -S 01-29 12:10 -D 50 | 61 | 0.109 | #ausopen, #australianopen, #federer, #rogerfederer, #18 |