[R] Νeed help changing my approach to my BSc thesis (Deep Learning, NLP, classification)
I want to get involved with whichever task of classification (sentiment analysis, hate speech, etc.) regarding text data, by using deep learning for my bachelor thesis.
I am confused about what should be the aim of the dissertation. I mean, I am not capable to come with something ground breaking or fancy (eg. A new complicated architecture). Beyond building some architectures from papers and testing data on them, what can I do in order to make the thesis more interesting?
Something I have thought of, is to create a pipeline that will retrieve tweets from the Twitter API from different locations and then pass them to a trained model in order to perform some kind of classification and then create a visualization of the world map regarding the topic (eg. brexit-preferences of each country). However, this doesn’t make a lot of sense since that procedure could be done more naively by counting specific hashtags on a geographical location. Also, how the dataset could be created and labeled?
Can you help me reconstruct my idea or guide me to a better direction?