Deception involves emotions of fear and guilt. These negative emotions are expressed in language in terms of psychological distance from the deception object. The psychological distance and emotional experience reflect an attempt to control the negative mental representation. More especifically emotional distance is represented in deceptive language by means of cues of reference, verb tense and detail avoidance. Then, hints of emotions of fear and guilt should be displayed in language.The present work analyses emotional language cues for deception detection by means of Machine Learning(ML) techniques and Linguistic Inquiry and Word Count (LIWC). Results show that Support Vector Machines (SVM) best represents the discrimination between true and false information (up to 74.15 % of accuracy rates) based only on the effect of emotion in deceptive speech.