Comparing different approaches to text analysis - talk at m3 London

Based on a publicly available standard data set, we will give a short overview of traditional methods of text analysis, focusing on supervised classifcation and unsupervised methods like topic modelling. Then we will turn to more sophisticated embedding methods and compare word2vec, GloVe, fastText, ELMo and BERT (and maybe more which are invented during 2019) with their specific strengths and weaknesses. We evaluate these in terms of intended use, computing time requirements and result quality.

Link to the talk: