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Using Speech Acts to Elicit Positive Emotions for Complainants on Social Media

Young Anna Argyris, Kafui Monu, Yongsuk Kim, Yilu Zhou, Zuhui Wang and Zhaozheng Yin

Journal of Interactive Marketing, 2021, vol. 55, issue C, 67-80

Abstract: A carefully tailored tone in response to a complaint on social media can create positive emotions for an upset customer. However, very few studies have identified what response tones, based on an established theory, would be most effective for complaint management. This study conceptualizes a service agent's response tones based on Ballmer and Brennenstuhl's (1981) classification of speech acts and examines how an agent's use of speech acts elicit positive emotions for the complainant. Ballmer and Brennenstuhl classify speech acts within the dimensions of conventionality and dialogicality, and they suggest the two dimensions interact. Thus, we examine the impact of each dimension of speech acts and the interactions between the two dimensions on the elicitation of positive emotions for complainants. We collected over 100,000 tweets and classified firm agents' speech acts and complainants' emotions by designing deep learning architectures (i.e., bi-directional recurrent neural networks). Our fixed-effect regression results show that a low level of each speech act leads to the elicitation of customers' positive emotions but that the combination of the two erodes the individual advantages. This study expands Ballmer and Brennenstuhl's (1981) speech act classification from a speaker's perspectives to a listener's perspectives by contextualizing it in an analysis of service agents' tones and their roles in eliciting positive emotions among complainants.

Keywords: Complaint management; Social media; Deep learning algorithm; Speech act theory (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:joinma:v:55:y:2021:i:c:p:67-80

DOI: 10.1016/j.intmar.2021.02.001

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