Investigating the emotional appeal of fake news using artificial intelligence and human contributions
| Date | 06 May 2019 |
| DOI | https://doi.org/10.1108/JPBM-12-2018-2179 |
| Published date | 06 May 2019 |
| Pages | 223-233 |
| Author | Jeannette Paschen |
| Subject Matter | Marketing |
Investigating the emotional appeal of
fake news using artificial intelligence and
human contributions
Jeannette Paschen
Department of Industrial Marketing, Kungliga Tekniska Hogskolan, Stockholm, Sweden
Abstract
Purpose –The creation and dissemination of fake news can have severe consequences for a company’s brand. Researchers, policymakers and
practitioners are eagerly searching for solutions to get us out of the “fake news crisis”. Here, one approach is to use auto mated tools, such as
artificial intelligence (AI) algorithms, to support managers in identifying fake news. The study in this paper demonstrates how AI with its ability to
analyze vast amounts of unstructured data, can help us tell apart fake and real news content. Using an AI application, this study examines if and
how the emotional appeal, i.e., sentiment valence and strength of specific emotions, in fake news content differs from that in real news content.
This is important to understand, as messages with a strong emotional appeal can influence how content is consumed, processed and shared by
consumers.
Design/methodology/approach –The study analyzes a data set of 150 real and fake news articles using an AI application, to test for differences
in the emotional appeal in the titles and the text body between fake news and real news content.
Findings –The results suggest that titles are a strong differentiator on emotions between fake and real news and that fake news titles are
substantially more negative than real news titles. In addition, the results reveal that the text body of fake news is substantially higher in displaying
specific negative emotions, such as disgust and anger, and lower in displaying positive emotions, such as joy.
Originality/value –This is the first empirical study that examines the emotional appeal of fake and real news content with respect to the
prevalence and strength of specific emotion dimensions, thus adding to the literature on fake news identification and marketing communications. In
addition, this paper provides marketing communications professionals with a practical approach to identify fake news using AI.
Keywords Brand communication, Message framing, Machine learning, Emotional appeal, Natural language processing, Emotional branding,
Communication model, Real news, Fake news, Artificial intelligence (AI)
Paper type Research paper
1. Fake news and brand communications
“When a headline asks a question, the answer should be no”.
Although this may read like a bizarre or even humorous
statement, this adage even has a name: Betteridge’s law
(Betteridge, 2009). Formulated by the British journalist Ian
Betteridge, it is based on the notion that journalists use this
style of headline if “they know the story is probably bullshit,
and don’t actually have the sourcesand facts to back it up, but
still want to run it”(Betteridge, 2009). This quote certainly
rings true today. For example, a 2017 article from
YourNewsWire claimed that accordingto an NPR study, more
than 25 million Hillary Clinton votes were fraudulent,
suggesting that Clinton had actually lost the popular vote by a
huge margin. This claimwas false and the study in question was
never conducted by NPR; still, it was among the most viral
stories shared on Facebook in 2017. Although not a new
phenomenon, the generation and impact of fake news and alt-
facts have reached new heights, driven mainlyby the increasing
digitization of information and the explosion of social media
(Baccarellaet al., 2018;Berthon and Pitt, 2018).
Fake news, defined as news that intentionally present
misinformation with the intent to deceive the audience (Bakir
and McStay, 2018;Horne and Adali, 2017;Kumar andShah,
2018), also known as disinformation(Hannah et al., 2015), can
have severe consequences for brands, businesses and societies
as a whole. A prime example is the 2016 US presidential
election and the concern about how false stories on social
media may have impacted the election outcome (Allcott and
Gentzkow, 2017). This has led a number of commentators
from reputable news outlets to suggest that Trump would not
have been elected without the influence of fake news (Dewey,
2016;Olson, 2016;Parkinson, 2016;Read, 2016). As a well-
informed public is key to any effective democracy, fake news
can be especially dangerous in the context of public opinion
and political information.
In addition, brands can also be impacted by and impact fake
news in a number of ways (Berthon and Pitt, 2018). First,
brands can be the direct target of false stories with major
consequences: Pepsi’s stock declined 4 per cent when a fake
news story about its CEO telling Trump supporters to “take
their business elsewhere”went viral.Second, brands can affect
Thecurrentissueandfulltextarchiveofthisjournalisavailableon
Emerald Insight at: https://www.emerald.com/insight/1061-0421.htm
Journal of Product & Brand Management
29/2 (2020) 223–233
© Emerald Publishing Limited [ISSN 1061-0421]
[DOI 10.1108/JPBM-12-2018-2179]
Received 26 December 2018
Revised 21 February 2019
Accepted 22 February 2019
223
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