Kevin Chow Kye Ven, Adeline Ng Khai Ying, Ngoo Qi Jie, Shoo Yen Lun, Scott Lee Chuen Yuen, D. Handayani, N. Hamzah, M. Lubis, T. Mantoro
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Depression Identification Through Social Media Posts: Data Preprocessing for Data Visualization of Tweets
Nowadays, mental health can be defined as a primary concern with the increased awareness related to the emergence of many campaigns to keep the body remaining healthy from the aspects that may be ignored. Therefore, the signs of deterioration are not always clear to be seen. Thus, social media is a safe space where many individuals often share their inner self, true feelings and honest impression. This is especially true of one of the popular social media platforms, Twitter. This paper explores the possibility of predicting the occurrence of depression in individuals through posts made. The results of the data pre-processing will be displayed through data visualization techniques.