Abstract
Drug addiction remains one of the key problems, which troubles each nation nowadays. Though social and economic
factors have been contributing to its escalation significantly, recently in recent years a marked rise with drug addiction
has witnessed in Iraq. Governments and societies are therefore working hard to find ways of counteracting this trend.
Notably, social media networks have become major conduits of the dissemination sensitization about the risks involved
in substance abuse addiction as well as consequences that are faced by drug abusers users. On the other hand, there
are no studies analyzing user’s sentiment regarding drug addiction on social media in Iraq. This paper offers a new
approach to fill this gap by presenting an analytical framework for identifying such sentiments of people from posts
published on different popular platforms including Facebook and Twitter. In order to achieve this, a new dataset was
generated from one of the relevant Facebook pages and comprised three distinct levels of user engagement data. Our
goal is to create a direct connection between the research objectives and practical applications which can benefit society.
This study’s results contribute significantly to the understanding of sentimental movements regarding drug addiction
and affect public perceptions on this significant problem. This study makes contributions to such fields are sentiment
analysis, social media research and public health by revealing the complex interaction of social media itself, user’s
feelings towards it or even drug addiction in Iraq. The new approach to analysis of multi-level user engagement data and
offers an evidence based solution for dealing with the challenges presented by drug abuse in society. Using a neural
network algorithm, the classification model developed has shown excellent performance with an accuracy rate of about
91%.