Understanding Miscommunication: Speech Act Recognition in Digital Contexts

Holtgraves, Thomas

doi:10.1111/cogs.13023

Cited by 10 publications

(6 citation statements)

References 52 publications

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“…The ability to use language to, in some instances, explain more than half of the variation in customer evaluations of their customer-firm interactions is a powerful tool to be leveraged within the customer service industry. As customers heavily rely on the use of language to perform specific speech acts in online reviews, they do so within a network of interpersonal structures, motives and feelings (Holtgraves, 2021). Linguistically, these elements most likely play a critical role in the communication process as well as how firms would be able to interpret and process their evaluations of the customer-firm interaction.…”

Section: Discussionmentioning

confidence: 99%

The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis

Ferreira

Robertson²,

Chohan³

et al. 2023

JSTP

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PurposeThis methodological paper demonstrates how service firms can use digital technologies to quantify and predict customer evaluations of their interactions with the firm using unstructured, qualitative data. To harness the power of unstructured data and enhance the customer-firm relationship, the use of computerized text analysis is proposed.Design/methodology/approachThree empirical studies were conducted to exemplify the use of the computerized text analysis tool. A secondary data analysis of online customer reviews (n = 2,878) in a service industry was used. LIWC was used to conduct the text analysis, and thereafter SPSS was used to examine the predictive capability of the model for the evaluation of customer-firm interactions.FindingsA lexical analysis of online customer reviews was able to predict evaluations of customer-firm interactions across the three empirical studies. The authenticity and emotional tone present in the reviews served as the best predictors of customer evaluations of their service interactions with the firm.Practical implicationsComputerized text analysis is an inexpensive digital tool which, to date, has been sparsely used to analyze customer-firm interactions based on customers' online reviews. From a methodological perspective, the use of this tool to gain insights from unstructured data provides the ability to gain an understanding of customers' real-time evaluations of their service interactions with a firm without collecting primary data.Originality/valueThis research contributes to the growing body of knowledge regarding the use of computerized lexical analysis to assess unstructured, online customer reviews to predict customers' evaluations of a service interaction. The results offer service firms an inexpensive and user-friendly methodology to assess real-time, readily available reviews, complementing traditional customer research. A tool has been used to transform unstructured data into a numerical format, quantifying customer evaluations of service interactions.

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Section: Discussionmentioning

confidence: 99%

The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis

Ferreira

Robertson²,

Chohan³

et al. 2023

JSTP

View full text Add to dashboard Cite

show abstract

“…Receivers were first asked to interpret the message/emoji by choosing from a list of 32 different speech acts. The list of speech acts was chosen from prior research (Holtgraves, 2021) and included an equal number of directives, expressives, commissives, and assertives. Receivers also indicated: (1) whether they thought they had correctly interpreted the message (1 = Yes ; 2 = No ) and (2) and their confidence that they had correctly interpreted the intended message (1 = Extremely unconfident to 9 = Extremely confident ).…”

Section: Methodsmentioning

confidence: 99%

Emoji, Speech Acts, and Perceived Communicative Success

Holtgraves

2023

Journal of Language and Social Psychology

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Unlike prior research examining how emoji communicate emotions and modify intended meanings, the present research examined whether emoji can perform specific speech acts (remind, etc.), and how well users are able to accurately assess their ability to do so. In four experiments senders were asked to assume that they would send a specific emoji to perform a certain speech act, or to choose which emoji they would use to perform that speech act. Senders and receivers indicated their judgments of communicative success (i.e., that the receiver would recognize the speech act being performed). In two studies, receivers also made judgments regarding the intended meaning of the emoji. Participants judged receivers to be likely to recognize the intended meaning conveyed with an emoji, and there was some evidence of communicative success. However, participants significantly overestimated communicative success, and in all studies, receivers were more optimistic about communicative success than were senders.

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“…Politeness is an important phenomenon in human social interaction. It is a linguistic phenomenon that serves social functions in dialogues, but can also lead to misunderstandings ( Holtgraves, 2021 ) because it stands in opposition to the cooperative principles underlying effective communication ( Grice, 1975 ; Franke and Jäger, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Should robots be polite? Expectations about politeness in human–robot interaction

Lumer,

Buschmeier

2023

Front. Robot. AI

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Interaction with artificial social agents is often designed based on models of human interaction and dialogue. While this is certainly useful for basic interaction mechanisms, it has been argued that social communication strategies and social language use, a “particularly human” ability, may not be appropriate and transferable to interaction with artificial conversational agents. In this paper, we present qualitative research exploring whether users expect artificial agents to use politeness—a fundamental mechanism of social communication—in language-based human-robot interaction. Based on semi-structured interviews, we found that humans mostly ascribe a functional, rule-based use of polite language to humanoid robots and do not expect them to apply socially motivated politeness strategies that they expect in human interaction. This study 1) provides insights for interaction design for social robots’ politeness use from a user perspective, and 2) contributes to politeness research based on the analysis of our participants’ perspectives on politeness.

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Understanding Miscommunication: Speech Act Recognition in Digital Contexts

Cited by 10 publications

References 52 publications

The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis

The writing is on the wall: predicting customers' evaluation of customer-firm interactions using computerized text analysis

Emoji, Speech Acts, and Perceived Communicative Success

Should robots be polite? Expectations about politeness in human–robot interaction

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