I want to train a binary classification algorithm for spam detection using labeled data set of mentions from social media. These mentions have the following features:URL, text message, posting date, is deleted, authorwhere the author has its own fields:URL, nick, type (person or community), number of subscribers, registration date, last activity dateI have $\approx 13.5k$ observations with $\approx 450$ spam messages among them. My suggestions: transform data features in real numbersbinarize URLs by media sources (e.g. facebook, instagram, etc.)use SVM with Gaussian kernel for all dataQuestions: Am I on the right way? What else can I do? How can I process text data?Thanks in advance for any suggestions!
Spam detection in social media
machine learning;classification;social network analysis