def prep_tweet_body(tweet_obj, args, processed_text):
    """ Format the incoming tweet

    Args:
        tweet_obj (dict): Tweet to preprocess.
        args (list): Various datafields to append to the object.
            0: subj_sent_check (bool): Check for subjectivity and sentiment.
            1: subjectivity (num): Subjectivity result.
            2: sentiment (dict): Sentiment result.
        processed_text (list): List of tokens and ngrams etc.

    Returns:
        dict: Tweet with formatted fields
    """

    subj_sent_check = args[0]
    result = tweet_obj

    if subj_sent_check:
        subjectivity = args[1]
        sentiment = args[2]
        result["subjectivity"] = subjectivity
        result["compound_score"] = sentiment["compound"]
        result["neg_score"] = sentiment["neg"]
        result["neu_score"] = sentiment["neu"]
        result["pos_score"] = sentiment["pos"]

    result["hs_keyword_count"] = len(processed_text[4])
    result["hs_keyword_matches"] = processed_text[4]
    result["tokens"] = processed_text[0]
    result["stopwords"] = processed_text[1]
    result["hashtags"] = processed_text[2]
    result["user_mentions"] = processed_text[3]
    result["unigrams"] = processed_text[5][0]
    result["bigrams"] = processed_text[5][1]
    result["trigrams"] = processed_text[5][2]
    result["quadgrams"] = processed_text[5][3]
    result["pentagrams"] = processed_text[5][4]
    result["stopword_ngrams"] = processed_text[6]
    result["ordered_tokens"] = processed_text[7]

    return result