pandas get "single" keywords from DataFrame string search

this is a follow-up of this previous topic. I have a Series of strings w called "British" like this:

British
\bSkilful\b
\bWilful\b
\bfulfil\b
\b.*favour.*\b
\bappal\b
\bappall.*\b
\barbour.*\b
\barmor.*\b
\bstrange\b
\brumor.*\b
\b.*color.*\b
\b.*centre's\b

and a DataFrame df like this:

 User_ID     Tweet
 01          hi all
 02          see you something
 03          that's my favourite spot
 04          the strangest rumors
 05          my appal is nice
 06          check my rumor
 07          #brborboncheckruMoreThanever
 08          look @mycentre's

I would like to get a new column containing the SINGLE keywords found in the strings. So far I did:

 List = pd.read_csv('w.txt')
 r = re.compile(r'.*({}).*'.format('|'.join(List['British'].values)), re.IGNORECASE)

and then mask the DataFrame:

  masked = map(bool, map(r.search, df['Tweet']))
  df2 = df[masked]

Then I masked it again to add the 'keyword' column:

 mask = [m.group(1) if m else None for m in map(r.search, df2['Tweet'])]
 df2['keyword'] = mask

which returns:

   User_ID                     Tweet         keyword
2        3  that's my favourite spot  favourite spot
4        5          my appal is nice           appal
5        6            check my rumor           rumor
7        8          look @mycentre's      mycentre's

So the boolean mask works fine and detect only the tweets containing at least one keyword. But what if I would like to extract only the single keyword found? The final DataFrame should be as:

   User_ID                     Tweet         keyword
2        3  that's my favourite spot       favourite
4        5          my appal is nice           appal
5        6            check my rumor           rumor
7        8          look @mycentre's        centre's

Thanks so much for your kind help.