I'm trying read in a whole article, separate the article by sentences, and then words. Then I pass this into the Word2vec Model and the output comes out.
However, my goal is to find the positive or negative sentiment of the article. The input is unsupervised in that it does not have a label.
Do I need to perform some sentiment scoring on the article before inputting into the word2Vec. I don't understand how word2vec actually helps with sentimental analysis. All it tells me is that words are close together/ have same context, but not actually whether the words are positive or negative.
I've read articles claiming to "use word2vec for sentimental analysis", but none actually do, so I'm not sure if I am misreading something here.
I'm wondering how I should go about this. Thanks.