SmokEng: Towards Fine-grained Classification of Tobacco-related Social Media Text
Table 1: Label and ID associated with each class.
['[BOLD] Name', '[BOLD] Label', '[BOLD] Annotation Class']
These categories were chosen on the basis of frequency of occurrence, motivated by the general perception of tobacco and non-tobacco drug related tweets. These included advertisements as well anecdotes, information and cautionary tweets. We further noticed that a similar pattern was seen for e-cigarettes and also pertained to some other drugs. While we have explored e-cigarettes in this classification, we have marked the mention of other drugs that were tagged with the same keywords.