Assessing the Emotional Arcs of Online Tourism Stories

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Abstract

Online storytelling has become a powerful destination promotion strategy as it effectively conveys information and at the same time involves travelers emotionally through inspiring imagination. With the development of advanced machine learning techniques, sentiment analysis has grown considerably where it now can be used to assess the emotions of social and other forms of text-based information. This study used sentiment analyses to examine the emotional arcs of 284 online tourism stories published on a number of American destination websites. Specifically, we first classified the stories into a set of dominant emotional arcs and then examined the differences in key website navigational behaviors. The results of these analyses clearly demonstrate that online stories which are emotionally charged but vary throughout the story are much more likely to increase reader involvement and therefore are more persuasive.

 

Assessing the Emotional Arcs of Online Tourism Stories

Online storytelling has become a powerful destination promotion strategy as it effectively conveys information and at the same time involves travelers emotionally through inspiring imagination. With the development of advanced machine learning techniques, sentiment analysis has grown considerably where it now can be used to assess the emotions of social and other forms of text-based information. This study used sentiment analyses to examine the emotional arcs of 284 online tourism stories published on a number of American destination websites. Specifically, we first classified the stories into a set of dominant emotional arcs and then examined the differences in key website navigational behaviors. The results of these analyses clearly demonstrate that online stories which are emotionally charged but vary throughout the story are much more likely to increase reader involvement and therefore are more persuasive.