Artificial Intelligence (AI) applications involved in all human- life activies. AI applications should be used in repetitive activities like inventory and supplies however many people use the AI applications in creative and human cantered actions. Many previous researchers discussed the importance of using AI in different fields like Education, supply chain, marketing, medical and engineering. Limited research focuses on using AI applications like ChatGPT in creating academic articles through idea creation, writing, proofreading, collecting data and analysing. It is very interesting to understand the academics opinions in using ChatGPT not only in learning and education but also in creating academic articles and whether ChatGPT can increase the productivity of the writing and help academics who are involved in many other tasks like teaching, examining, preparing curriculums, assisting projects and managing quality procedures. The paper will propose Academics Emotion Analysis Model that will analyse the sentiments of academics whether they agree to use ChatGPT in writing articles or not. Word2vec and Term Frequency Inverse Document Frequency (TFIDF) and word2vec feature selection methods will be used and three machine learning techniques which are Naive Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) on 17,000 sentiments. Academics emotion analysis model will start with the processing academics sentiments and using feature selection method then will use three-machine learning. Results including precision, recall and accuracy of all these classifiers will be described in this paper with a highest accuracy equivalent to 94% in Word2vec feature selection method by NB classifier. The paper will help understanding the Egyptian Academics’ opinion on using ChatGPT in article creation process.