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• Article | Organizational Behavior and Human Decision Processes

  Conversational Receptiveness: Expressing Engagement with Opposing Views

  M. Yeomans, J. Minson, H. Collins, H. Chen, F. Gino, M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino

  We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then show that in contentious policy discussions, government executives who were rated as more receptive—according to our algorithm and their partners but not their own self-evaluations—were considered better teammates, advisors, and workplace representatives (Study 2). Furthermore, using field data from a setting where conflict management is endemic to productivity, we show that conversational receptiveness at the beginning of a conversation forestalls conflict escalation at the end. Specifically, Wikipedia editors who write more receptive posts are less prone to receiving personal attacks from disagreeing editors (Study 3). We develop a “receptiveness recipe” intervention based on our algorithm. We find that writers who follow the recipe are seen as more desirable partners for future collaboration and their messages are seen as more persuasive (Study 4). Overall, we find that conversational receptiveness is reliably measurable, has meaningful relational consequences, and can be substantially improved using our intervention.

  Keywords: receptiveness; natural language processing; disagreement; Interpersonal Communication; Relationships; Conflict Management;

  Citation:

  Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.  View Details

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• Article | Organizational Behavior and Human Decision Processes

  Conversational Receptiveness: Expressing Engagement with Opposing Views

  M. Yeomans, J. Minson, H. Collins, H. Chen, F. Gino, M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino

  We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then show that in contentious policy discussions, government executives who were rated as more receptive—according to our algorithm and their partners but not their own self-evaluations—were considered better teammates, advisors, and workplace representatives (Study 2). Furthermore, using field data from a setting where conflict management is endemic to productivity, we show that conversational receptiveness at the beginning of a conversation forestalls conflict escalation at the end. Specifically, Wikipedia editors who write more receptive posts are less prone to receiving personal attacks from disagreeing editors (Study 3). We develop a “receptiveness recipe” intervention based on our algorithm. We find that writers who follow the recipe are seen as more desirable partners for future collaboration and their messages are seen as more persuasive (Study 4). Overall, we find that conversational receptiveness is reliably measurable, has meaningful relational consequences, and can be substantially improved using our intervention.

  Keywords: receptiveness; natural language processing; disagreement; Interpersonal Communication; Relationships; Conflict Management;

  Citation:

  Yeomans, M., J. Minson, H. Collins, H. Chen, and F. Gino. "Conversational Receptiveness: Expressing Engagement with Opposing Views." Organizational Behavior and Human Decision Processes 160 (September 2020): 131–148.  View Details

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• Article | Journal of Personality and Social Psychology | July 2020

  Tell It Like It Is: When Politically Incorrect Language Promotes Authenticity

  J. Schroeder, M. Rosenblum and F. Gino

  When a person’s language appears political—such as being politically correct or incorrect—it can influence fundamental impressions of him or her. Political correctness is “using language or behavior to seem sensitive to others’ feelings, especially those others who seem socially disadvantaged.” One pilot study, six experiments, and three supplemental experiments (N = 4,956) demonstrate that being politically incorrect makes communicators appear more authentic—specifically, less susceptible to external influence—albeit also less warm. These effects, however, are moderated by perceivers’ political ideology and how sympathetic perceivers feel toward the target group being labeled politically correctly. In Experiments 1, 2, and 3 using politically incorrect language (e.g., calling undocumented immigrants “illegals”) made a communicator appear particularly authentic among conservative perceivers but particularly cold among liberal perceivers. However, in Experiment 4 these effects reversed when conservatives felt sympathetic toward the group that was being labeled politically correctly or incorrectly (e.g., calling poor whites “white trash”). Experiment 5 tests why political incorrectness can boost authenticity, demonstrating that it makes communicators seem less strategic. Finally, Experiment 6 tests our hypothesis in an externally valid field context: exploring the impact of politically incorrect language on perceived persuasion in real political debates. Debaters instructed to be politically incorrect (vs. politically correct) were judged by their uninstructed conversation partners to be less easily persuaded during the conversation, although they actually reported being similarly persuaded. Together, these findings demonstrate when and how using politically incorrect language can enhance a person’s authenticity.

  Keywords: language; Interpersonal Communication; Perception;

  Citation:

  Schroeder, J., M. Rosenblum, and F. Gino. "Tell It Like It Is: When Politically Incorrect Language Promotes Authenticity." Journal of Personality and Social Psychology 119, no. 1 (July 2020): 75–103.  View Details

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