1. A method of utilizing natural language processing (NLP) to analyze data logs, the method comprising: generating a data log in response to executing a software application, wherein the data log includes a plurality of entries that each comprise debugging data generated from execution of the software application; performing a sentiment analysis on the data log, wherein the sentiment analysis further comprises: identifying at least one negative connotation corresponding to at least one term located in at least a selected one of the plurality of entries; determining that the selected entry is within a predetermined spatial proximity of at least one known error message in the data log; and generating a proximity model score in response to the determination; generating a sentiment score for the selected entry based upon the proximity model score; and identifying for visual highlighting the selected entry based on the sentiment score.