Training data in sentiment analysis

Question

I'm doing sentiment analysis of tweets related to recent acquisition of Twitter by Elon Musk. I have a corpus of 10 000 tweets and I'd like to use machine learning methods using models like SVM and Linear Regression. My question is, when I want to train the models, do I have to manually tag big portion of those 10 000 collected tweets with either positive or negative class to train the model correctly or can I use some other dataset of tweets not relating to this topic that's already tagged to train the model for sentiment analysis? Thank you for your answers!