But even from a human's perspective emotions are hard to identify and track, hence for a computer to identify accurate emotions can be challenging.

Ideally if a computer can identify a human's emotions and respond to it accordingly human computer interactions would be much more natural and more convenient.

With upcoming developments emotion identification is an important aspect in HCI. Based on the results, we discuss the advantages of using an automated e-counselling system for emotion analysis.Įmotional intelligence is the ability to understand changing states of emotion, it is an important aspect of human interaction. We speculate, based on the findings, that the emotional state of counsellors influences their emotion perception while tracking emotions in text. Furthermore, the intra-annotation agreement of emotions was found to be strongly correlated to the counsellors’ self-reported emotions. The result shows strong intra-counsellor annotation agreement of emotions while inter-counsellors annotation agreement was low. This influence is investigated through the level of agreement among counsellors when annotating emotions expressed in students’ personal life’s stories. In this paper, we explore empirically, the extent to which counsellors own emotional states influence their perception of emotions expressed in text. Therefore, ascertaining the efficacy of computational algorithm, there is the need to benchmark with humans. And this highlights the need for complementing the intuitional effort of counsellors by computational approach. Therefore, the accuracy of detected emotions by counsellors could be doubtful. Since counsellors are humans we assume that their own state of emotions could affect their intuitional effort when taking decisions concerning their clients. Emotions are a core semantic component of human communication.

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