Your first query was pretty close. To remove the unwanted stemming, create a text search configuration with a simple dictionary that does not do it.
I suggest to use a separate schema for text search objects, but that's totally optional:
CREATE SCHEMA ts;
GRANT USAGE ON SCHEMA ts TO public;
COMMENT ON SCHEMA ts IS 'text search objects';
CREATE TEXT SEARCH DICTIONARY ts.english_simple_dict (
TEMPLATE = pg_catalog.simple
, STOPWORDS = english
);
CREATE TEXT SEARCH CONFIGURATION ts.english_simple (COPY = simple);
ALTER TEXT SEARCH CONFIGURATION ts.english_simple
ALTER MAPPING FOR asciiword WITH ts.english_simple_dict; -- 1, 'Word, all ASCII'
Then your query works, and very fast, too:
SELECT *
FROM ts_stat($$SELECT to_tsvector('ts.english_simple', title) FROM item$$)
ORDER BY ndoc DESC
LIMIT 50;
dbfiddle here
This operates with lower case words without stemming and doesn't break for non-ASCII letters.
Backgroud
Read the chapter Simple Dictionary in the manual.
The exact definition of a "word" is a tricky matter. The default text search parser (currently it's the only one) identifies 23 different types of tokens. See:
SELECT * FROM ts_token_type('default');
Built-in text search configurations map most of those to (built-in) dictionaries. Mappings for the english config:
SELECT tt.*, m.mapdict::regdictionary AS dictionary
FROM pg_ts_config_map m
LEFT JOIN ts_token_type(3722) tt ON tt.tokid = m.maptokentype
WHERE mapcfg = 'english'::regconfig -- 'ts.english_simple'::regconfig
ORDER BY tt.tokid;
The demo above creates a new config based on the simple config, and since all English stop words are of type 'asciiword', we only need to map this type to remove stop words, no stemming or anything else.