The Language of Coalition Formation in Online Multiparty Negotiations

Huffaker, David A.; Swaab, Roderick I.; Diermeier, Daniel

doi:10.1177/0261927x10387102

Cited by 52 publications

(65 citation statements)

References 32 publications

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“…For example, higher levels of linguistic mimicry increase romantic interest between individuals who are speed-dating (Ireland et al 2011), increase preferences for products (Tanner et al 2008), and increase team performance, trust, and cohesion (Gonzales et. al 2010;Huffaker et al 2011;Swaab, Maddux and Sinaceur 2011). However, linguistic mimicry can also decrease the likelihood of reaching an agreement in competitive interactions (Ireland and Henderson 2014), and mimicry of negative emotion words decreases trust in dyadic interactions (Scissors, Gill, Geraghty, and Gergle 2010).…”

Section: Behavioral and Linguistic Mimicrymentioning

confidence: 99%

She Said, She Said: Differential Interpersonal Similarities Predict Unique Linguistic Mimicry in Online Word of Mouth

Moore¹,

McFerran²

2017

Journal of the Association for Consumer Research

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3This research examines the antecedents, causes, and consequences of linguistic mimicry, which assesses how closely individuals match others' word use, in online WOM. We examine mimicry of both linguistic style (how things are said) and content (what is said). To our knowledge, this research provides the first demonstration of unique linguistic mimicry, where consumers engaging in online WOM differentially mimic other posters' word use. Two experiments and one study using field data show that when consumers are personally similar to an individual who has previously posted (e.g., same gender), they mimic this individual's positive emotion and social word use. When consumers are similar in status to an individual who has previously posted (e.g., same forum ranking), they mimic this individual's cognitive and descriptive word use. This differential mimicry is driven by affiliation versus achievement goals, respectively, and affects consumers' engagement in online WOM in terms of posting incidence and volume.

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Section: Behavioral and Linguistic Mimicrymentioning

confidence: 99%

She Said, She Said: Differential Interpersonal Similarities Predict Unique Linguistic Mimicry in Online Word of Mouth

Moore¹,

McFerran²

2017

Journal of the Association for Consumer Research

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“…Categories related to power dynamics were also explored: certainty words (always, never) are used by those in power positions (Magee, Milliken & Lurie, 2010), assent words (agree, OK) aid in negotiations (Huffaker, Swaab & Diermeier, 2011) and use of auxiliary verbs (e.g., "a mistake was made but I don't blame anyone") are, by definition use of a passive voice.…”

Section: Linguistic Markersmentioning

confidence: 99%

Everyday Confrontation of Discrimination: The Well-Being Costs and Benefits to Women over Time

Foster¹

2013

IJPS

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Taking action against discrimination has positive consequences for well-being (e.g., Cocking & Drury, 2004) but most of this research has focused on collective actions and has used methodologies assessing one point in time. This study therefore used a diary methodology to examine how women's everyday confrontations of discrimination would affect measures of subjective and psychological well-being, and how these relationships would change over time. In a 28-day online diary study, women indicated their daily experience of discrimination, described their response, and completed measures of well-being. Results showed that at the beginning of the study, using indirect confrontation predicted greater well-being than using angered confrontation. However, continued use of indirect and educational confrontation decreased well-being whereas continued use of angered confrontation increased well-being over time. By the end of the study, using angered confrontation predicted greater well-being than using indirect confrontation. Analyses of linguistic markers were consistent with the explicit measures of well-being. Implications for distinguishing between types of confrontations and integrating time analyses are discussed.

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“…The convergent use of similar linguistic styles enhances understanding and perceptions of a common social identity while decreasing perceptions of social distance [53]. In online textbased negotiations, closer matches in function word usage (e.g., uses of pronouns, articles, conjunctions, prepositions, auxiliary verbs, high-frequency adverbs, negations, and quantifiers) as part of the interactional exchange increase interpersonal rapport and agreement among potential partners [44]. Although in B2B communication, partners may naturally accommodate each other's communication style due to genuine liking, their tendency to do so immediately and rapidly ought to be weaker.…”

Section: Meta-level Deception Cuesmentioning

confidence: 99%

Untangling a Web of Lies: Exploring Automated Detection of Deception in Computer-Mediated Communication

Ludwig

Laer

Ruyter

et al. 2016

Journal of Management Information Systems

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Safeguarding organizations against opportunism and severe deception in computer-mediated communication (CMC) presents a major challenge to chief information officers and information technology managers. New insights into linguistic cues of deception derive from the speech acts innate to CMC. Applying automated text analysis to archival e-mail exchanges in a CMC system as part of a reward program, we assess the ability of word use (micro level), message development (macro level), and intertextual exchange cues (meta level) to detect severe deception by business partners. We empirically assess the predictive ability of our framework using an ordinal multilevel regression model. Results indicate that deceivers minimize the use of referencing and self-deprecation but include more superfluous descriptions and flattery. Deceitful channel partners also overstructure their arguments and rapidly mimic the linguistic style of the account manager across dyadic e-mail exchanges. Thanks to its diagnostic value, the proposed framework can support firms’ decision making and guide compliance monitoring system development

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The Language of Coalition Formation in Online Multiparty Negotiations

Cited by 52 publications

References 32 publications

She Said, She Said: Differential Interpersonal Similarities Predict Unique Linguistic Mimicry in Online Word of Mouth

She Said, She Said: Differential Interpersonal Similarities Predict Unique Linguistic Mimicry in Online Word of Mouth

Everyday Confrontation of Discrimination: The Well-Being Costs and Benefits to Women over Time

Untangling a Web of Lies: Exploring Automated Detection of Deception in Computer-Mediated Communication

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