Watch list of Tweets with unknown model I have a pre-trained model that I load after import gensim using model = KeyedVectors.load_word2vec_format('path', binary = True).
It has 46 000 words in 25 dimension vector space. I don't know anything about the model used to obtain such vectors.
I also have a 75-word watch list that all but one belong to model 's vocabulary.
I want to monitor tweets from ABC and XYZ for &quot;matches&quot; associated with my watch list.
How can I monitor scraped tweets for terms in my word list ? I do not know what to make of their vector representation in model, nor what to do with my word that's not in the vocabulary
There are several steps:

Setup a system that collects tweets from certain accounts.
Preprocess the tweets to create tokens that similar to the tokens in the pretrained model (e.g., lowercase and/or stem).
Create two sets of watch list tokens and tweet tokens. Take the intersection of the two sets.

There are two options for tokens that in tweets but not in pretrained model:

Ignore them.
Explicitly model them as &quot;UNK&quot; / unknown