How to go about text mining for suggestions/Tips in reviews for restaurants? For example for restaurants reviews usually have suggestions like "Go in the evenings", "order the so and so sauce with this dish"  or even "TIP: ask for the blah blah blah"

How can I detect such sentences? How do people usually tackle similar challenges? 

Do they create classification rules like &lt;modal_verb&gt;&lt;preference_verb&gt;&lt;optional_window_size_of_3&gt;&lt;positive_sentiment_words&gt;
Some examples of these rules are “would be great” and “could be really good”  --
 found this from here.

I guess I would have to use a tagger to categorize words?

Any blog that has attempted something similar step by step?

Any help would appreciated.
So the way I thought about it is - abstractly you are attempting to identify which sentences are, Imperative Mood (IMP) and which are not. One option is to put together a training set/validation set, where each row is a phrase's pos tags (can use some encoder to convert to integers) with a target value of 'isImperative' (binary) then train a model and restructure each review so that they resemble the training set format and have your model assign the values. Seems the easiest and most sustainable method from where I am sitting. Sorry but I don't know any easily accessible phrase data sets but I bet there is one out there somewhere. Hope this helps.