How do I use recency/time as a feature after I've a word2vec model
The purpose of the Word2vec is it will itself learn a hidden structure in your text data. If "recovery" comes after rap and music is because Eminem is more frequent with these context words than with recovery. You can't simply change that. You should avoid making a manual intervention on your model.

However, here are 2 ideas you could try if you really want "recovery" to be closer of Eminem word :


Try an other Word2Vec algorithm architecture. There are CBOW and skip-gram you can try. In my opinion CBOW could perform better because the CBOW model trains each word against its context. It asks "given this set of context words, what missing word is likely to also appear at the same time?". Skip-gram trains each the context against the word. It asks "given this single word, what are the other words that are likely to appear near it at the same time?"
Add sentences relative to recovery album in your data. Because words recovery and Eminem should dominate in these sentences, It could reconcile the 2 words. Same, you can replicate sentences containing both Eminem and recovery word and randomly change the order of words in the sentence.