Zhijun Zhang¹, Austin Amakye Ansah² and Ang Li³, ¹Columbia International College, Canada, ²The University of Texas at Arlington, USA, ³California State Polytechnic University, USA

Some people keep journals to track their mental health or keep a record of things happening in their lives [9]. While journaling can help identify patterns in mood and tackle stress and anxiety at the root cause, only 8 percent of the population do it. With the 8.58 billion mobile subscriptions in use worldwide, we take advantage of mobile applications to deliver a quick on-the-go solution for mobile journaling that can be used free of charge [10]. This application utilizes NLP to determine user mood and provide tasks and goals that the user can work towards to improve their well-being. The NLP model developed in this paper has an accuracy of about 91% in correctly classifying moods on a sequence of words in a validation dataset. The model is good enough for most text-based emotional sentiment analysis needs but could be re-trained to attain better results.