Anastazia Žuni?|Padraig Corcoran|?Irena Spasi?
Sentiment Analysis in Health and Well-Being: Systematic Review
Cardiff University|Cardiff University|Cardiff University
sentiment analysis sa subfield natural language processing whose aim automatically classify sentiment expressed free text found practical applications across wide range societal contexts including marketing economy politics review focuses specifically applications related health defined state complete physical mental social wellbeing merely absence disease infirmitythis study aimed establish state art sa related health wellbeing conducting systematic review recent literature capture perspective individuals whose health wellbeing affected focused specifically spontaneously generated content necessarily health care professionalsour methodology based guidelines performing systematic reviews january 2019 used pubmed multifaceted interface perform literature search medline identified total 86 relevant studies extracted data datasets analyzed discourse topics data creators downstream applications algorithms used evaluationthe majority data collected social networking webbased retailing platforms primary purpose online conversations exchange information provide social support online communities tend form around health conditions high severity chronicity rates different treatments services discussed include medications vaccination surgery orthodontic services individual physicians health care services general identified 5 roles respect health wellbeing among authors types spontaneously generated narratives considered review sufferer addict patient carer suicide victim 86 studies considered 4 reported demographic characteristics wide range methods used perform sa common choices included support vector machines nave bayesian learning decision trees logistic regression adaptive boosting contrast general trends sa research 1 study used deep learning performance lags behind state art achieved domains measured fscore found 60 average context sa domain health wellbeing found resource poor domainspecific corpora lexica shared publicly research purposessa results area health wellbeing lag behind domains yet unclear intrinsic differences domains respective sublanguages size training datasets lack domainspecific sentiment lexica choice algorithms