MEANING OF SENTIMENT ANALYSIS FOR COMPANIES

Abstract

People often ask others for product advice. Once, word-of-mouth (WOM) was, due to practical limitations, shared locally.  Nowadays, WOM is shared online (eWOM), which has a much larger reach.  As eWOM is publicly accessible (unlike WOM), it can be used as information on brand attitude.  eWOM can be aggregated and assessed using sentiment analysis (identifying positive/negative messages). The assumption is that sentiment analysis illustrates people's brand perception. We investigate the relationship between sentiment analysis and brand perception.  We collected tweets with sentiment information of eight brands in Indonesia using Twitter's built-in sentiment analysis over a week.  Using these tweets, aggregated sentiment scores were computed. The scores were correlated with brand perception collected using questionnaires. 206 participants attributed scores to seven properties: Complaint handling, Design, Friendliness, Information, Marketing, Service, and Overall score.  Either insignificant or correlations close to zero were found, so online sentiment does not correspond to offline brand perception.

Keywords: word-of-mouth, artificial intelligence in business, sentiment analysis