Offinsive tweets classification
The task to be completed within this project is to develop and evaluate a system that processes
a single tweet and decides whether or not the tweet contains offensive language. This task
could be tackled as a binary text classification problem. To this end, a dataset of
tweets annotated for offensiveness is provided in the repo. The files “train.tsv” and “dev.tsv” all have the same format.
The second column (text) contains the text of a tweet, the first column (label) contains an
(NOT) Not Offensive - This post does not contain offense or profanity.
(OFF) Offensive - This post contains offensive language or a targeted (veiled or direct)
The table below shows a few examples of tweets that
have been annotated as offensive.
1 @USER Liberals are all Kookoo !!!
2 @USER @USER Most stupid tweet yet…and yes…its a libtard
3 @USER I bet the first ones she calls when she is being robbed is those
very same police . People are freaking stupid …
4 @USER @USER Go home you’re drunk!!! @USER #MAGA #Trump2020 URL
Naive bayes and svm classifiers were used as models. link to the repo.