Abstract: A machine learning engine may correlate contextual information associated with a misspelling in a publication with a likelihood that the misspelling is intentional in nature. Training data may be generated by analyzing one or more past publication to identify misspellings and labeling the misspellings as intentional. A contextual indicators application may analyze the context in which intentional misspellings have been previously included within publication to identify indicators of future misspellings being intentional. A machine learning engine may use the training data and indicators to generate an intentional linguistic deviation (ILD) prediction model to determine whether a new misspelling is an intentional misspelling. The machine learning engine may also determine weights for individual indicators that may calibrate the influence of the respective individual indicators.