SENTIMENT ANALYSIS IN TWITTER DATA

Abstract

With the recent growth of mobile information systems and the increased availability of smart phones, social media has become a large part of daily life in most societies. This development has entailed the creation of massive amounts of data: data which when analysed can be used to extract valuable information about a variety of subjects. Sentiment analysis (SA), also known as opinion mining is the process of classifying the emotion conveyed by a text, for example as negative, positive or neutral. The data made available by social media has contributed to a burst of research activity within SA in recent times and a shift in the focus of the field towards this type of data. Information gained from applying SA to social media data has many potential usages, for instance, to help marketers evaluate the success of an ad campaign, to identify how different demographics have received a product release, to predict user behaviour, or to forecast election results.