Building text sentiment classifier for posts and comments in social media networks.
With the rise of various social platforms, user-generated content on the web is increasing, generating a large amount of textual information, such as news, microblogs, blogs, etc. Faced with such huge and emotionally expressive textual information, it is entirely possible to consider serving people by exploring their potential value. We will extract reviews from different fields, such as game reviews, movie reviews, news reviews, etc., analyze their emotional tendencies (we will classify emotional tendencies as positive to negative), and explore the information they contain.