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Figure from:Rumor Psychology Social and Organizational Approaches

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Note. Each genre of communication may exhibit all contexts, contents, and functions in this table (e.g., rumor also functions to impart cultural mores and gossip also functions to help the group make sense of ambiguity), though each genre’s quintessential contexts, contents, and functions are listed here. Rumor activity in ambiguous contexts therefore functions to make sense; it is a response to the core human motivation to understand (Fiske, 2004). The resolving of ambiguity is always a sense-making explanation of events that are unclear for some part of a group or community. As G. W. Allport and Postman put it in their seminal text, The Psychology of Rumor, “in ordinary rumor we find a marked tendency for the agent to attribute causes to events, motives to characters, a raison d'etre to the episode in question” [italics in original] (1947b, p. 121). Explanations primarily attempt to make reality perceptible and mean- ingful (Antaki, 1988); rumors are a collective effort at such explanations when a group—or subset of a group—is faced with uncertainty (Di- Fonzo & Bordia, 1998). To some extent, these explanations must pass some group norm of plausibility. When group standards of plausibility are high, rumor discussions look very much like fact finding. When the group standards are low, rumor discussions look very much like contagion or panic. Rumor is thus part of “normal collective information seeking” [italics in original] (R. H. Turner, 1994, p. 247) wherein the group is trying to define an ambiguous situation with a “lower degree
Note. Each genre of communication may exhibit all contexts, contents, and functions in this table (e.g., rumor also functions to impart cultural mores and gossip also functions to help the group make sense of ambiguity), though each genre’s quintessential contexts, contents, and functions are listed here. Rumor activity in ambiguous contexts therefore functions to make sense; it is a response to the core human motivation to understand (Fiske, 2004). The resolving of ambiguity is always a sense-making explanation of events that are unclear for some part of a group or community. As G. W. Allport and Postman put it in their seminal text, The Psychology of Rumor, “in ordinary rumor we find a marked tendency for the agent to attribute causes to events, motives to characters, a raison d'etre to the episode in question” [italics in original] (1947b, p. 121). Explanations primarily attempt to make reality perceptible and mean- ingful (Antaki, 1988); rumors are a collective effort at such explanations when a group—or subset of a group—is faced with uncertainty (Di- Fonzo & Bordia, 1998). To some extent, these explanations must pass some group norm of plausibility. When group standards of plausibility are high, rumor discussions look very much like fact finding. When the group standards are low, rumor discussions look very much like contagion or panic. Rumor is thus part of “normal collective information seeking” [italics in original] (R. H. Turner, 1994, p. 247) wherein the group is trying to define an ambiguous situation with a “lower degree
Note. UM/H = low, medium, or high. Hypothesized Information Dimensions of Rumor, News, Gossip, and Urban Legend
Note. UM/H = low, medium, or high. Hypothesized Information Dimensions of Rumor, News, Gossip, and Urban Legend
Mean information dimension ratings for exemplars of rumor, gossip, news, and urban legend: evidentiary basis, importance, about individuals, and slanderous.
Mean information dimension ratings for exemplars of rumor, gossip, news, and urban legend: evidentiary basis, importance, about individuals, and slanderous.
Mean information dimension ratings for exemplars of rumor, gossip, news, and urban legend: entertaining and useful.
Mean information dimension ratings for exemplars of rumor, gossip, news, and urban legend: entertaining and useful.
-xample of a display presented on a training “day.” From “Rumors and Stable Cause Attribution in Prediction and Behavior,” by N. DiFonzo and P. Bordia, 2002b, Organiza- ‘ional Behavior and Human Decision Processes, 88, p. 787. Copyright 2002 by Elsevier. Reprinted with permission.
-xample of a display presented on a training “day.” From “Rumors and Stable Cause Attribution in Prediction and Behavior,” by N. DiFonzo and P. Bordia, 2002b, Organiza- ‘ional Behavior and Human Decision Processes, 88, p. 787. Copyright 2002 by Elsevier. Reprinted with permission.
Rumor effects and mean severity ratings. Effects are in decreasing order by the percent- age of respondents (n ranged from 66—73) who had ever observed the effect in their overall experience. Mean severity ratings are on a scale in which 1, 2, and 3 indicate small, medium, and large average effects, respectively. F indicates an external ramifica- tion, A indicates effects related to internal attitudes, and B indicates effects associated with internal behaviors (see text). From “How Top PR Professionals Handle Hearsay: Corporate Rumors, Their Effects, and Strategies to Manage Them,” by N. DiFonzo and P. Bordia, 2000, Public Relations Review, 26, p. 180. Copyright 2000 by Elsevier. Reprinted with permission. Average severity rating, as well as the percentage of the sample that had ever observed the effects, is presented in Figure 2.2. Our experienced sample had observed a large majority of the effects during their long tenures; each of the top 11 effects had been witnessed by at least 78% of the sample. The most commonly experienced— 90% or greater—rumor effects included detrimental consequences for employee morale, press reports, productivity, stress levels, and trust held by employees and customers. Effects were rated, overall, as moderately severe: 13 of the 17 effects were given an average severity rating between 1.50 and 2.50 (indicating medium severity). The most severe of these—those with an average rating at or above 1.75—
Rumor effects and mean severity ratings. Effects are in decreasing order by the percent- age of respondents (n ranged from 66—73) who had ever observed the effect in their overall experience. Mean severity ratings are on a scale in which 1, 2, and 3 indicate small, medium, and large average effects, respectively. F indicates an external ramifica- tion, A indicates effects related to internal attitudes, and B indicates effects associated with internal behaviors (see text). From “How Top PR Professionals Handle Hearsay: Corporate Rumors, Their Effects, and Strategies to Manage Them,” by N. DiFonzo and P. Bordia, 2000, Public Relations Review, 26, p. 180. Copyright 2000 by Elsevier. Reprinted with permission. Average severity rating, as well as the percentage of the sample that had ever observed the effects, is presented in Figure 2.2. Our experienced sample had observed a large majority of the effects during their long tenures; each of the top 11 effects had been witnessed by at least 78% of the sample. The most commonly experienced— 90% or greater—rumor effects included detrimental consequences for employee morale, press reports, productivity, stress levels, and trust held by employees and customers. Effects were rated, overall, as moderately severe: 13 of the 17 effects were given an average severity rating between 1.50 and 2.50 (indicating medium severity). The most severe of these—those with an average rating at or above 1.75—
Note. N = 63. Printed values are multiplied by 100 and rounded to the nearest integer. Component loadings greater than 0.50 have been flagged by an asterisk (*). From “How Top PR Professionals Handle Hearsay: Corpo- rate Rumors, Their Effects, and Strategies to Manage Them,” by N. DiFonzo and P. Bordia, 2000, Public Relations Review, 26, p. 181. Copyright 2000 by Elsevier. Reprinted with permission.
Note. N = 63. Printed values are multiplied by 100 and rounded to the nearest integer. Component loadings greater than 0.50 have been flagged by an asterisk (*). From “How Top PR Professionals Handle Hearsay: Corpo- rate Rumors, Their Effects, and Strategies to Manage Them,” by N. DiFonzo and P. Bordia, 2000, Public Relations Review, 26, p. 181. Copyright 2000 by Elsevier. Reprinted with permission.
Mean number of rumors heard, employee uncertainty, anxiety, self-rated productivity, and intention to stay during an organizational downsizing. relation varied widely from month to month (ry, = ~.32 for T2 and T4
Mean number of rumors heard, employee uncertainty, anxiety, self-rated productivity, and intention to stay during an organizational downsizing. relation varied widely from month to month (ry, = ~.32 for T2 and T4
Mean number of rumors heard, perceptions of communication quality, perceptions of management as caring and trustworthy, job satisfaction, and organizational commit- ment during an organizational downsizing.
Mean number of rumors heard, perceptions of communication quality, perceptions of management as caring and trustworthy, job satisfaction, and organizational commit- ment during an organizational downsizing.
general, the ingroup audience was the preferred target in all conditions, except when the rumor was positive in valence and about the outgroup. Second, contrary to the MUM effect, when the rumor was about the ingroup and the recipient was a member of the ingroup, both positive and negative rumors were equally likely to be transmitted. In other words, participants did not hesitate to transmit negative rumor to an ingroup recipient. We expected the fact-finding motivation to underlie this effect. To test this idea, we conducted a mediation analysis that tested the effect of rumor recipient (ingroup vs. outgroup) on likelihood of transmission, when the rumor was negative and about the ingroup. We predicted that participants were more likely to transmit a negative rumor about the ingroup to ingroup recipients (as compared with out- group recipients) because they wanted to know if the rumor was true. Our prediction was partly supported: The effect of rumor recipient on likelihood of transmission was partially mediated by the fact-finding motivation.*
general, the ingroup audience was the preferred target in all conditions, except when the rumor was positive in valence and about the outgroup. Second, contrary to the MUM effect, when the rumor was about the ingroup and the recipient was a member of the ingroup, both positive and negative rumors were equally likely to be transmitted. In other words, participants did not hesitate to transmit negative rumor to an ingroup recipient. We expected the fact-finding motivation to underlie this effect. To test this idea, we conducted a mediation analysis that tested the effect of rumor recipient (ingroup vs. outgroup) on likelihood of transmission, when the rumor was negative and about the ingroup. We predicted that participants were more likely to transmit a negative rumor about the ingroup to ingroup recipients (as compared with out- group recipients) because they wanted to know if the rumor was true. Our prediction was partly supported: The effect of rumor recipient on likelihood of transmission was partially mediated by the fact-finding motivation.*
Self-enhancement motivation in conditions of positive versus negative rumor about the ingroup or the outgroup when the recipient is from the ingroup or the outgroup. RIT = Rochester Institute of Technology; UofR = University of Rochester.
Self-enhancement motivation in conditions of positive versus negative rumor about the ingroup or the outgroup when the recipient is from the ingroup or the outgroup. RIT = Rochester Institute of Technology; UofR = University of Rochester.
ingroup vs. outgroup) on likelihood of transmission to an outgroup member.
ingroup vs. outgroup) on likelihood of transmission to an outgroup member.
Note. nr = not reported. na = not applicable. *Refers to the overall percentage of communication details that could be assessed as true or false, which were true in a rumor or set of rumors. Refers to Davis's summarization of his own research (i.e., several studies). ‘Refers to the percentage of correct responses of those attributed to grapevine information on a 12-question quiz administered to employees. Choices included a “don't know” op- tion, however, which garnered between 35% and 77% per question (M = 52%), thus limiting the 82% accuracy figure to those responses for which the employees felt “reasonably” certain of their answers (Walton, 1961, pp. 48-49). ‘Prasad (1935) presented a “representative set” of 30 rumors, 23 of which were verifiable (i.e., dealt with empirical as opposed to metaphysical events).
Note. nr = not reported. na = not applicable. *Refers to the overall percentage of communication details that could be assessed as true or false, which were true in a rumor or set of rumors. Refers to Davis's summarization of his own research (i.e., several studies). ‘Refers to the percentage of correct responses of those attributed to grapevine information on a 12-question quiz administered to employees. Choices included a “don't know” op- tion, however, which garnered between 35% and 77% per question (M = 52%), thus limiting the 82% accuracy figure to those responses for which the employees felt “reasonably” certain of their answers (Walton, 1961, pp. 48-49). ‘Prasad (1935) presented a “representative set” of 30 rumors, 23 of which were verifiable (i.e., dealt with empirical as opposed to metaphysical events).
of 244 rumors.’ One hundred thirty-seven rumors were true; 107 were false. To assess more closely the types of change occurring in true and false rumors, we computed the frequency of the verity-precision combinations for this sample; these are presented in Figure 6.2. The results are very similar to those of Student Survey 1. We first observe that the overwhelming majority of rumors were all or mostly true or false; there appeared to be little middle ground for rumors that had since been proven true or false. Of the all or mostly true rumors recalled, most by far resembled converts. Of those that proved all or mostly
of 244 rumors.’ One hundred thirty-seven rumors were true; 107 were false. To assess more closely the types of change occurring in true and false rumors, we computed the frequency of the verity-precision combinations for this sample; these are presented in Figure 6.2. The results are very similar to those of Student Survey 1. We first observe that the overwhelming majority of rumors were all or mostly true or false; there appeared to be little middle ground for rumors that had since been proven true or false. Of the all or mostly true rumors recalled, most by far resembled converts. Of those that proved all or mostly
Note. ST = serial transmission.
Note. ST = serial transmission.
Note. MI = multiple interaction (see text). 4p < .10. * p<.05. **p < .01. ***p < .001.
Note. MI = multiple interaction (see text). 4p < .10. * p<.05. **p < .01. ***p < .001.
Hypothesized moderating role of trust on uncertainty—transmission and anxiety- transmission relationships.
Hypothesized moderating role of trust on uncertainty—transmission and anxiety- transmission relationships.
Note. N = 60 for T1-1T1 correlations; N = 46, 47, or 48 for all other correlations. LOT = likelihood of transmission (proportion of heard rumors transmitted). Uncertainty and anxiety were transformed prior to correlation calcula- tions. Alpha coefficients are in the diagonal. No alpha coefficients for T1 or T2 LOT could be computed because these were single-item measures. *p < .05. **p < .01. Operationalizing rumor transmission in this way is appropriate given a number of different rumors in circulation over a period of time—a condition typical of organizationa LOT is independent of the number of rumors that a particular individual hears. The advantage of this independence considers that the alternative operationa passed—depends in large par on the num rumor episodes. In addition, becomes apparent when one ization—number of rumors ber of rumors that one hears; LOT accounts for this confound by being a within-subjects variable. By extension, LOT also accounts for factors of rumors heard, such as w 1972) and whether or not one is part o 1965). Therefore, LOT affords the advantage that the results that obtain in this investigation cannot number of rumors heard. known to affect the number hether or not one is a liaison (K. Davis, a close network (Buckner, be caused by factors associated with the
Note. N = 60 for T1-1T1 correlations; N = 46, 47, or 48 for all other correlations. LOT = likelihood of transmission (proportion of heard rumors transmitted). Uncertainty and anxiety were transformed prior to correlation calcula- tions. Alpha coefficients are in the diagonal. No alpha coefficients for T1 or T2 LOT could be computed because these were single-item measures. *p < .05. **p < .01. Operationalizing rumor transmission in this way is appropriate given a number of different rumors in circulation over a period of time—a condition typical of organizationa LOT is independent of the number of rumors that a particular individual hears. The advantage of this independence considers that the alternative operationa passed—depends in large par on the num rumor episodes. In addition, becomes apparent when one ization—number of rumors ber of rumors that one hears; LOT accounts for this confound by being a within-subjects variable. By extension, LOT also accounts for factors of rumors heard, such as w 1972) and whether or not one is part o 1965). Therefore, LOT affords the advantage that the results that obtain in this investigation cannot number of rumors heard. known to affect the number hether or not one is a liaison (K. Davis, a close network (Buckner, be caused by factors associated with the
Computed slopes of regression line (predictor: T1 anxiety; outcome: T1 likelihood of transmission [LOT]) at sample low, average, and high T1 trust in the company.
Computed slopes of regression line (predictor: T1 anxiety; outcome: T1 likelihood of transmission [LOT]) at sample low, average, and high T1 trust in the company.
Computed slopes of regression line (predictor: T1 anxiety; outcome: T2 likelihood of transmission [LOT]) at sample low, average, and high T1 trust in the company.
Computed slopes of regression line (predictor: T1 anxiety; outcome: T2 likelihood of transmission [LOT]) at sample low, average, and high T1 trust in the company.
Mean belief reduction, anxiety reduction, and source appropriateness ratings for rumor denials issued by sources that varied in appropriateness. Rumor that the grade point average required for entry into second-year undergraduate courses will be going up next year. Data from Bordia et al., 1998. Student Lecturer t Head of Department & Vice Chancellor
Mean belief reduction, anxiety reduction, and source appropriateness ratings for rumor denials issued by sources that varied in appropriateness. Rumor that the grade point average required for entry into second-year undergraduate courses will be going up next year. Data from Bordia et al., 1998. Student Lecturer t Head of Department & Vice Chancellor
was therefore an organization-level topic, the VC was considered the
was therefore an organization-level topic, the VC was considered the
Integrative model of rumor.
Integrative model of rumor.