Role of affect in marketplace rumor propagation
02 Sep 2019-Marketing Intelligence & Planning (Emerald Publishing Limited)-Vol. 37, Iss: 6, pp 631-644
TL;DR: In this paper, the authors explored the role of positive affect and negative affect in rumor sharing behavior among consumers and found that positive affect has a stronger influence on rumor sharing as compared to negative affect.
Abstract: Rumors about products and brands are common occurrence in the marketplace. Often these rumors are shared among consumers using the word of mouth channel. The spread of these rumors is fast and can lead to significant consequences to products and brands. The purpose of this paper is to explore the dynamics of such rumor sharing behavior among consumers. Specifically, this paper investigates the role of positive affect and negative affect in rumor sharing behavior. Three key rumor characteristics (valence, involvement and credibility) are explored as antecedents to positive affect and negative affect.,The paper collects data from 236 respondents using Amazon MTurk, and conducts a PLS–SEM analysis to explore the role of positive affect and negative affect in rumor sharing contexts.,Both positive affect and negative affect were found to be significant factors leading to rumor sharing, furthermore positive affect was found to have a stronger influence on rumor sharing as compared to negative affect. The study also delineates the role of valence, involvement and credibility in rumor sharing scenarios, all of which have a strong role in shaping positive affect and negative affect.,The study is novel in using cognitive appraisal theory to illustrate the formation of positive affect and negative affect in rumor encounters. The study conclusively illustrates the role of cognitive appraisal and emotional experiences in the rumor propagation context, and advances the marketing scholarship’s understanding significantly.
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TL;DR: The authors found that people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks, and that the average American adult saw on the order of one or perhaps several fake news stories in the months around the 2016 U.S. presidential election, with just over half of those who recalled seeing them believing them.
Abstract: Following the 2016 U.S. presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: (i) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; (ii) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; (iii) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and (iv) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.
3,959 citations
TL;DR: It appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.
Abstract: PurposeHealth-related online fake news (HOFN) has become a major social problem. HOFN can lead to the spread of ineffective and even harmful remedies. The study aims to understand Internet users' responses to HOFN during the coronavirus (COVID-19) pandemic using the protective action decision model (PADM).Design/methodology/approachThe authors collected pandemic severity data (regional number of confirmed cases) from government websites of the USA and China (Studies 1 and 2), search behavior from Google and Baidu search engines (Studies 1 and 2) and data regarding trust in two online fake news stories from two national surveys (Studies 2 and 3). All data were analyzed using a multi-level linear model.FindingsThe research detected negative time-lagged relationships between pandemic severity and regional HOFN search behavior by three actual fake news stories from the USA and China (Study 1). Importantly, trust in HOFN served as a mediator in the time-lagged relationship between pandemic severity and search behavior (Study 2). Additionally, the relationship between pandemic severity and trust in HOFN varied according to individuals' perceived control (Study 3).Originality/valueThe authors' results underscore the important role of PADM in understanding Internet users' trust in and search for HOFN. When people trust HOFN, they may seek more information to implement further protective actions. Importantly, it appears that trust in HOFN varies with environmental cues (regional pandemic severity) and with individuals' perceived control, providing insight into developing coping strategies during a pandemic.
8 citations
TL;DR: In this paper, the authors proposed an extension to TAM to analyse the significance of monetary benefits and information reliability on customers' intention to use social media, while information reliability and monetary benefits significantly influence only through perceived usefulness.
Abstract: The present study intends to shed light on behaviour of customers towards usage of social media for purchasing decisions. The study proposes an extension to technology acceptance model (TAM) to analyse the significance of monetary benefits and information reliability on customers' intention to use social media.,The sample was drawn from social media users of north-western region of India (n = 622). The proposed model was tested using exploratory factor analysis and structural equation modelling.,Results indicate that monetary benefits and perceived ease of use have significant influence on customers' intention to use social media, while information reliability and monetary benefits significantly influence only through perceived usefulness.,The findings are valuable to marketers to acknowledge the potential of social media to reach to masses by providing timely and reliable information. The study also reveals that website/app developers should implement a user-friendly interface and reliable content to influence customers' usage behaviour.,The study is a unique attempt to examine the effect of monetary benefits and information reliability with TAM's key constructs in the context of social media adoption. Studies undertaken aforementioned dimensions are mainly concerned with examining direct contribution of social media and its effect on purchase decisions.
6 citations
TL;DR: This article provided a systematic and structured overview of the factors that influence the spread of misinformation by analyzing the four vital elements of information communication, namely, source, message, context, and receiver.
6 citations
References
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TL;DR: Findings indicate that MTurk can be used to obtain high-quality data inexpensively and rapidly and the data obtained are at least as reliable as those obtained via traditional methods.
Abstract: Amazon's Mechanical Turk (MTurk) is a relatively new website that contains the major elements required to conduct research: an integrated participant compensation system; a large participant pool; and a streamlined process of study design, participant recruitment, and data collection. In this article, we describe and evaluate the potential contributions of MTurk to psychology and other social sciences. Findings indicate that (a) MTurk participants are slightly more demographically diverse than are standard Internet samples and are significantly more diverse than typical American college samples; (b) participation is affected by compensation rate and task length, but participants can still be recruited rapidly and inexpensively; (c) realistic compensation rates do not affect data quality; and (d) the data obtained are at least as reliable as those obtained via traditional methods. Overall, MTurk can be used to obtain high-quality data inexpensively and rapidly.
9,562 citations
TL;DR: The convergence and differentiation criteria, as applied by Bagozzi, are shown not to stand up under mathematical or differentiation criteria.
Abstract: Several issues relating to goodness of fit in structural equations are examined. The convergence and differentiation criteria, as applied by Bagozzi, are shown not to stand up under mathematical or...
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TL;DR: In this article, a generalized form of the cross-validation criterion is applied to the choice and assessment of prediction using the data-analytic concept of a prescription, and examples used to illustrate the application are drawn from the problem areas of univariate estimation, linear regression and analysis of variance.
Abstract: SUMMARY A generalized form of the cross-validation criterion is applied to the choice and assessment of prediction using the data-analytic concept of a prescription. The examples used to illustrate the application are drawn from the problem areas of univariate estimation, linear regression and analysis of variance.
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Abstract: Reanalyses of a number of studies of self-reported mood indicate that Positive and Negative Affect consistently emerge as the first two Varimax rotated dimensions in orthogonal factor analyses or as the first two second-order factors derived from oblique solutions. The two factors emerged with varyi
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Abstract: The authors examine the effect of consumer reviews on relative sales of books at Amazon.com and Barnesandnoble.com. The authors find that (1) reviews are overwhelmingly positive at both sites, but there are more reviews and longer reviews at Amazon.com; (2) an improvement in a book's reviews leads to an increase in relative sales at that site; (3) for most samples in the study, the impact of one-star reviews is greater than the impact of five-star reviews; and (4) evidence from review-length data suggests that customers read review text rather than relying only on summary statistics.
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