9. A system for suggesting headline terms, comprising: a processor for executing program code; and non-transitory computer storage memory, storing program code that, when executed on the processor, causes the system to perform a method comprising: implementing a machine learning headline click-based topic model; training the machine learning headline click-based topic model using search logs and historic click through data to account for the potential of a word in a headline to induce a click; receiving an article and a headline associated with the article; determining a topic associated with the article; determining at least one word trending in the topic associated with the article; and determining a word click through rate for the at least one word trending in the topic using the trained machine learning headline click-based topic model.
9. A system for suggesting headline terms, comprising: a processor for executing program code; and non-transitory computer storage memory, storing program code that, when executed on the processor, causes the system to perform a method comprising: implementing a machine learning headline click-based topic model; training the machine learning headline click-based topic model using search logs and historic click through data to account for the potential of a word in a headline to induce a click; receiving an article and a headline associated with the article; determining a topic associated with the article; determining at least one word trending in the topic associated with the article; and determining a word click through rate for the at least one word trending in the topic using the trained machine learning headline click-based topic model. 10. The system of claim 9 , wherein the method further comprises: suggesting at least one word from among the at least one word trending in the topic based on its word click through rate.