def get_word2vec_related_words_from_word(word, model, threshold, max_qty):
	"""
	Method to generate a list of words that are found to be related to the input word through
	assessing similarity to other words in a word2vec model of word embeddings. The model can
	be learned from relevant text data or can be pre-trained on an existing source. All words
	that satisfy the threshold provided up to the quantity specified as the maximum are added.
	
	Args:
		word (str): The word for which we want to find other related words.
		
		model (Word2Vec): The actual model object that has already been loaded.
		
		threshold (float): Similarity threshold that must be satisfied to add a word as related.
		
		max_qty (int): Maximum number of related words to accept.
	
	Returns:
		list: The list of related words that were found, could be empty if nothing was found.
	"""
	
	related_words = []
	try:
		matches = model.most_similar(word, topn=max_qty)
	except KeyError:
		matches = []
	for match in matches:
		word_in_model = match[0]
		similarity = match[1]
		if (similarity >= threshold):
			related_words.append(word_in_model)
	return(related_words)