Abstract

An automated-based system has been developed in order to gather stories from iCanQuit. Similarly, using Twitter Streaming API, geolocated tweets within UK region have been collected during a three months period, and those related to smoking cessation, according to the semantic text matching, are extracted and stored in a database. An automated classifier has been employed to identify the four most dominant categories in Health field for each document of blogs or Twitter dataset. A total of 880 stories from iCanQuit and 22155 relevant tweets have been collected and indexed in SQLite database. The automated classifier highlighted four categories: Weight Loss, Mental Health, Addiction, Support Group. The analysis surprisingly reveals that both blogs and Twitter datasets agree that the dominant source of smoking cessation is related to weight loss (shape body appearance), or body-look, while the support group, which includes any clinician supports, plays little impact on the smokers’ quit motivation, a result that maybe precious for health authorities.