The Addition Symptoms Parameter on Sentiment Analysis to Measure Public Health Concerns
Abstract: Information about
public health has a very important role not only for health practitioners, but
also for goverment. The importance of health information can also affect the
emotional changes that occur in the community, especially if there is news
about the spread of infectious disease (epidemic) in particular area at the
time, such as case of outbreaks Ebola disease or Mers in specific area. Based
on data obtained from Semiocast, Indonesia is the country with fifth largest
number of Twitter users in the world, where every topic that lively discussed
will also influence a global trending topic. This paper will discuss the
measurement of public health concern (Degree of Concern) level by using
sentiment analysis classification on the twitter status. Sentiment data of the
tweets were analyzed and given some value by using a scoring method. The
scoring method equation (Kumar A. et al., 2012) will be tested with new additional
parameters, ie symptoms parameters. The value of any twitter user sentiment is
determined based on adjectives, verbs, and adverbs that contained in the
sentence. The method that we used to find the semantic value of adjectives is
corpus-based method. While for finding the semantic value of the verb and
adverb we used a dictionary-based method.
Author: Yohanssen Pratama
Journal Code: jptkomputergg170161
