DEPRESSION DETECTION USING SOCIAL NETWORKING SITES VIA DATA MINING
Keywords:
Depression detection, data mining, social media, PDD (Psychological Disorder Detection), OSN (Online Social Network), SNMD (Social Network Mental Disorder) classifier, feature extractionAbstract
Human emotions like depression are inner sentiments which are often exposed by the way the person
behaves. If such emotions can be analyzed and determined from the person's social activities in the virtual world, it
can be very helpful to understand these behaviors. To detect depressive moods, detecting words that express negativity
in their social media messages can be the first step. Depression doesn't just affect the person himself, it can affect his
friends, family, co-workers, and everyone around him. Also, it may have an impact on how he performs at work or his
concentration level in general; in short it can negatively affect productivity. To understand if a Facebook type system
user could exhibit depression over a period of time, then the system will be able to identify the depressed user based on
his activities like post and chats, which includes emotional type keywords.
