Boolean classification on strings
There are many approaches to this type of problem, which would be defined as text classification. You could create a Term Frequency or Term Frequency Inverse Document Frequency matrix based on the tokens (words) in the strings, then use standard machine learning algorithms such as SVM, Random Forest, Gradient Boosted Trees, Logistic Regression, Naive Bayes. You could also potentially use word embedding's and neural networks. In this case, each word would be represented as a vector of similar words. Finally, I have recently been experimenting with character level convolutional neural networks and this seems to work well for user generated text classification. There is link below.

https://papers.nips.cc/paper/5782-character-level-convolutional-networks-for-text-classification.pdf