Cross Intelligence Evaluation for Effective Emotional Intelligence Estimation

Abstract

: A famous psychologist or researcher, Daniel Goleman, gave a theory on the importance of Emotional Intelligence for the success of an individual’s life. Daniel Goleman quoted in the research that “The contribution of an individual’s Intelligence Quotient (IQ) is only 20% for their success, the remaining 80% is due to Emotional Intelligence (EQ)”. However, in the absence of a reliable technique for EQ evaluation, this factor of overall intelligence is ignored in most of the intelligence evaluation mechanisms. This research presented an analysis based on basic statistical tools along with more sophisticated deep learning tools. The proposed cross intelligence evaluation uses two different aspects which are similar, i.e., EQ and SQ to estimate EQ by using a trained model over SQ Dataset. This presented analysis ensures the resemblance between the Emotional and Social Intelligence of an Individual. The research authenticates the results over standard statistical tools and is practically inspected by deep learning tools. Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) and Social IQ dataset are deployed over a Multi-layered Long-Short Term Memory (M-LSTM) based deep learning model for accessing the resemblance between EQ and SQ. The M-LSTM based trained deep learning model registered, the high positive resemblance between Emotional and Social Intelligence and concluded that the resemblance factor between these two is more than 99.84%. This much resemblance allows future researchers to calculate human emotional intelligence with the help of social intelligence. This flexibility also allows the use of Big Data available on social networks, to calculate the emotional intelligence of an individual.