In examining Twitter data for such non-standard tokens, we found that 55.0% of them were types (1) to (3) in Table 1, 4.5% were type (4), 20.1% were types (5) to (6), 2.7% were type (7), and the rest did not fall under any of these types since they were the result of dialects, typos, and other factors.
a large majority of the non-standard tokens fell under types (1) to (7).