Researchers are concerned with automated personality detection from social media. Automated Personality detection from text benefits in social media like: attracting more users, career advising and getting more advertisements. Traditional personality detection is done by using an assessment test. Performing a test is time-consuming so users aren't interested in taking a test. This paper presents case study and architecture on automated personality from text using twitter text. The case study uses public text to identify the personality of the profile. The applied personality Model is the Enneagram model. Proposed architecture contains four phases: text preprocessing, feature extraction, feature selection and personality detection. Feature selection is done by using Enneagram ontology and lexicon. Personality detection is utilized by using statistical approaches. The Enneagram knowledge is modeled using ontology. The lexicon is a source to enrich the ontology seed. Statistical Approach is utilized to identify the personality. The case study identifies the personality. The highest outcome percentage is "investigator" personality, which is 24 %. This indicates that the personality is an investigator. This result is similar to official Enneagram experts' analysis. This model is the first one which uses the Enneagram model as automatic detection. Enneagram is a powerful personality model that aids psychiatrists and physicians to understand the patient's personality intensely. This knowledge gives them the tools to support and aid the patient to heal faster. The promising outcomes open the door to further research in this area.
Background: Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by longstanding airflow obstruction caused by emphysema or chronic bronchitis. 1 COPD is responsible for significant morbidity, early mortality, high death rates and substantial costs to the healthcare system. COPD is projected to be the third most frequent cause of death worldwide by 2020 and the fifth leading cause of years lost through early disability. 2 Elderly people are especially prone to the adverse health effects of chronic obstructive pulmonary disease (COPD), which is a common disorder in that population. Although the prevalence and morbidity of COPD in the elderly are high, it is often undiagnosed. 3 In its early stages COPD is sometimes missed, as COPD patients learn to limit their physical activities to escape the gradually emerging dyspnea on exertion. So
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.