rasel277144:

so are you suggesting I should take the average of the 10 embedding vectors?


Yes, that’s the idea  The goal is to create in some sense a single embedding for each user, so the quick 'n dirty way to do that is by averaging the embedding vectors of each post.
One drawback with this approach is that it will average out subtle correlations associated with each post and so you might need to try a weighted average (e.g. based on the post length or other potentially interesting criteria) to get good results.
Also, my experience has generally been that you get better results with fine-tuning, so I would also compare the embedding approach against the simplest thing of concatenating all the posts and truncating anything longer than the context size of the model (BERT, BigBird etc).