The shift to working from home, which has intensified due to Covid-19, increased our reliance on communication technology and the need to communicate effectively via computer-mediated communication and especially via text. Paralinguistic cues, such as repeated punctuation, are used to compensate for the lack of non-verbal cues in text-based formats. However, it is unclear whether these cues indeed bridge the potential gap between the writer’s intentions and the reader’s interpretations. A pilot study and two experiments investigated the effect of using (...) repeated punctuation on behavioral intention to assist an email writer in a work-related situation. Findings demonstrate that while the intentions behind using repeated punctuation relate to signaling situational importance or affective state, behavioral intentions are driven by dispositional rather than situational attributions. Specifically, the use of repeated punctuation reduces perceived competence of the message writer and consequently decreases positive behavioral intentions. Overall, the study challenges the simplified view of paralinguistic cues as communication facilitators, highlighting their potential harmful effects on impression formation and behavioral intentions in the digital age. (shrink)

Healey et al. use experiments with chat dialogues to test the hypothesis that language co‐ordination is driven by ‘running repairs’. They replace signals of understanding such as “okay” with weaker, ‘spoof’ signals like “ummm”, and replace specific requests for clarification like “on the left?” with signals that suggest a higher degree of misunderstanding like “what?”. The latter manipulation causes participants to switch rapidly to more abstract forms of referring expression.

The laugh- and/or smile-evoking potency of laughter was evaluated by observing responses of 128 subjects in three undergraduate psychology classes to laugh stimuli produced by a “laugh box.” Subjects recorded whether they laughed and/or smiled during each of 10 trials, each of which consisted of an 18-sec sample of laughter, followed by 42 sec of silence. Most subjects laughed and smiled in response to the first presentation of laughter. However, the polarity of the response changed quickly. By the 10th trial, (...) few subjects laughed and/or smiled, and most found the stimulus “obnoxious.” Although other research has described canned-laughter effects, it did not consider the hypothesis confirmed here, that laughter itself evokes laughter, perhaps by activating a laughter-specific auditory-feature detector. This result is relevant to the neurological basis of social communication, human ethology, and theories of speech production and perception. (shrink)

Science communication has gained high importance in the current knowledge and risk society. Nevertheless, there is still a lack of qualitative studies on how non-experts and experts engage in opinionated scientific debates and which linguistic devices they use to gain influence on other people’s attitudes toward a scientific issue. In our study, we examine dialogical modes of science communication (i.e. weblogs) used by bloggers and audiences to engage into opinionated discourse about scientific endeavors. As those exchanges easily lead to controversies (...) between different points of views, stances and attitudes, we focus from a rhetorically-driven linguistic perspective on devices to persuade the other participants and readers and to control the discourse. Hence, we ask which linguistic instruments are used to gain influence on influence. The aim of our study is to get deeper insights into the persuasive strategies mainly used in those forms of external science communication. (shrink)

In the near future, robots will function in social roles and attempt to influence the user’s behavior and / or thinking. The current contribution analyses how to influence robot influence: Persuasive robots can be personalized to make them more effective. We present an overview of (1) the user characteristics to which persuasive robots can be personalized, (2) considering the specific current situation of a user; and (3) the robot characteristics that can be personalized. Thereby, we give an overview of how (...) the persuasive robot’s physical appearance, behavior, (perceived) cognition and affect can be influenced to characteristics of the user (personalized) in order to make the robot more persuasive and thereby to understand better how the persuasive power of an embodied artificial social entity can be influenced. (shrink)

This study investigates interpersonal processes underlying dialog by comparing two approaches, interactive alignment and interpersonal synergy, and assesses how they predict collective performance in a joint task. While the interactive alignment approach highlights imitative patterns between interlocutors, the synergy approach points to structural organization at the level of the interaction—such as complementary patterns straddling speech turns and interlocutors. We develop a general, quantitative method to assess lexical, prosodic, and speech/pause patterns related to the two approaches and their impact on collective (...) performance in a corpus of task-oriented conversations. The results show statistical presence of patterns relevant for both approaches. However, synergetic aspects of dialog provide the best statistical predictors of collective performance and adding aspects of the alignment approach does not improve the model. This suggests that structural organization at the level of the interaction plays a crucial role in task-oriented conversations, possibly constraining and integrating processes related to alignment. (shrink)

In this paper, we analyze what effects indicators of a shared situation have on a speaker’s persuasiveness by investigating how a robot’s advice is received when it indicates that it is sharing the situational context with its user. In our experiment, 80 participants interacted with a robot that referred to aspects of the shared context: Face tracking indicated that the robot saw the participant, incremental feedback suggested that the robot was following their actions, and comments about, and gestures towards, the (...) shared physical situation and linguistic references to the dialog history indicated to participants that the robot had learned from the interaction and perceived its surroundings. The results show that especially the linguistic and gestural references to the shared context have a significant influence on participants’ compliance with the robot’s suggestions. Thus, indicating that it is ‘in the same boat’ with the user, i.e. that it is sharing the situational context, increases a robot’s persuasiveness during advice giving. (shrink)