I am working on a text dataset containing messages from users on a website. Please check the image in the link as stack is not allowing me to post this image directly. dataframe of the first five rows
Reading those messages i want to find out the intent of the users whether they are buyer, seller or neutral. I have tried topic modelling using both LDA and NMF but it's not giving me answers. As i am getting very different topics and i cannot find a way to relate it to buyer seller or neutral. And i cannot manually label these data because it's a huge dataset containing 200,000 thousands of rows. So which technique or algorithm can i use to solve this problem.