{'fraction_non_alphanumeric': 0.01616161616161616, 'fraction_numerical': 0.0, 'mean_word_length': 4.863905325443787, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Emotion Detection Using Unobtrusive methods: An Integrated Approach

Proven research is available to identify the importance of emotions in every walk of life. Emotions play an important role in a human's life in the sense that they effect how a user makes decisions, buys commodities, the way he lives in, the way he learns and many more. Emotion has been used as an attribute in many computational systems that provide services to mankind. Many affective systems have come into picture when the concept of personalized recommendations was realized. Affective systems are the systems that deal with the emotional nature of a user. The major question with these systems is the detection of emotion. The methods and the user characteristics that can be used to detection of emotion of the user. This paper proposes a unique methodology to detect emotions using the unobtrusive method of keystrokes, mouse clicks, forum discussions and results of assessments if any in an E-learning scenario.