You can use the invert (~) operator (which acts like a not for boolean data):
new_df = df[~df["col"].str.contains(word)]
where new_df is the copy returned by RHS.
contains also accepts a regular expression…
If the above throws a ValueError or TypeError, the reason is likely because you have mixed datatypes, so use na=False:
new_df = df[~df["col"].str.contains(word, na=False)]
Or,
new_df = df[df["col"].str.contains(word) == False]