Data mining on reviews of the games I am trying to text mine the reviews of the games and want to find the interesting things from the reviews
example of the data is 

'review': ['Simple yet with great replayability. In my opinion does "zombie" hordes and team work better than left 4 dead plus has a global leveling system. Alot of down to earth "zombie" splattering fun for the whole family. Amazed this sort of FPS is so rare.',
'Amazing, Non-stop action of blowing stuff to bits, Decapitation and shooting everything you see. With a combination of action, thriller and emmersive gameplay, as well as enviromental challanges (Jump physics). This game will really put your eyes to the test, can you see the enemys before they see you? Cause their are so many!This is the second level of the killing floor, I quote bill LF4D "Son we just crossed the street" But in reality they only moved up an elevator level on genes. What has yet to come as the game is slowly realsed with thrilling and horryfing creations, But who really cares, Let\'s just blow it up, I invite you to get on the GODAMN KILLING FLOOR, LET'S SHOOT  AND GET PAID!',......
]



I am interested to find the name of games and types of games(strategy, shooting, etc) from the reviews data.

I tried and created the regular expression such that getting the text which has data ( is a game )
so that I will get the reviews 

Dying Light is a game.
Magicka is a game



I want a suggestion to improve the results for the above 
and my interst is to text mine and find the game type such as a puzzle, shooting,etc
Suggestion to improve the results is to use NER. You can at very least extract names and types. Search a bit more maybe someone has also trained on different types/genres of game also, so you could discriminate on that also.