Page 149 - The Handbook of Persuasion and Social Marketing

The Impact of Word of Mouth and the Facilitative Effects of Social Media 141

attribution about the cause of the negativity, serve to attenuate the impact
of negative WOM. For example, Herr, Kardes, and Kim (1991) showed
that an established prior memory of the brand and/or the presence of ex-
tremely negative attribute information reduces or attenuates the impact of
negative WOM. In addition, when negative WOM is attributed to the
communicator (and not the brand), consumers tend not to decrease their
evaluation of the brand (Laczniak, DeCarlo, & Ramaswami, 2001). The
latter authors argued that these findings fit in nicely with those of Herr,
Kardes, and Kim (1991) because communicator-based attribution is pre-
sumably perceived as nondiagnostic by the consumer.
One can gain an understanding of why the common perception among
practitioners and academics is that negative WOM has significantly greater
impact than positive WOM. First, WOM information is “vivid” in the sense
that it is communicated face-to-face and, as defined by the American
Heritage Dictionary (1975), such information is “heard, seen or felt as if it
were real.” Second, negative information conveyed about a company or
product by others is diagnostic, in the sense that it is typically rarer than
positive information, and thus helps the consumer discriminate between
alternative hypotheses, interpretations, or categorizations (Herr, Kardes,
and Kim, 1991).
In an attempt to examine the underlying processes that regulate the ef-
fect of positive versus negative information, Ahluwalia (2002) examined
consumers’ written responses to familiar versus unfamiliar brands when
given information varying in valence about the brand. When the brand
was unfamiliar to the subject, the negative information elicited more sup-
porting arguments and was perceived to have more diagnosticity and
weight. Under the familiar brand condition, there was no significant dif-
ference in the impact of positive versus negative information in terms of
either weight or diagnosticity. Hence, consistent with the findings of Herr,
Kardes, and Kim (1991), Ahluwalia (2002) found that brand familiarity
mediated the impact of the diagnosticity of negative information on brand
evaluation. She further argued that for known brands, positive informa-
tion may potentially be perceived to be more diagnostic than negative in-
formation. Indeed if the weight of WOM being communicated in the field
is linked to known versus unknown brands, then the dearth of significant
effects for the impact of negative WOM is more easily understood.
Researchers have taken particular interest in the effect of social media
on predicting movie box office success as a function of information va-
lence versus quantity. For example, Asur and Huberman (2010) examined
the degree and polarity of “tweets” on movie sales, findings that the rate of
tweets was far more predictive than the polarity of the tweets. The findings