Investigating the emotional appeal of fake news using artificial intelligence and human contributions

被引:43
|
作者
Paschen, Jeannette [1 ]
机构
[1] Kungliga Tekniska Hogskolan, Dept Ind Mkt, Stockholm, Sweden
来源
关键词
Brand communication; Message framing; Machine learning; Emotional appeal; Natural language processing; Emotional branding; Communication model; Real news; Fake news; Artificial intelligence (AI); BRANDS; MEMORY; FACT;
D O I
10.1108/JPBM-12-2018-2179
中图分类号
F [经济];
学科分类号
02 ;
摘要
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 automated 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.
引用
收藏
页码:223 / 233
页数:11
相关论文
共 50 条
  • [1] Detecting fake news on Facebook: The role of emotional intelligence
    Preston, Stephanie
    Anderson, Anthony
    Robertson, David J.
    Shephard, Mark P.
    Huhe, Narisong
    [J]. PLOS ONE, 2021, 16 (03):
  • [2] Artificial Intelligence Blockchain Based Fake News Discrimination
    Kim, Seong-Kyu
    Huh, Jun-Ho
    Kim, Byung-Gyu
    [J]. IEEE ACCESS, 2024, 12 : 53838 - 53854
  • [3] Correction: Detecting fake news on Facebook: The role of emotional intelligence
    Preston, Stephanie
    Anderson, Anthony
    Robertson, David J.
    Shephard, Mark P.
    Huhe, Narisong
    [J]. PLOS ONE, 2021, 16 (10):
  • [4] Investigating the Difference of Fake News Source Credibility Recognition between ANN and BERT Algorithms in Artificial Intelligence
    Chiang, Tosti H. C.
    Liao, Chih-Shan
    Wang, Wei-Ching
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (15):
  • [5] Beyond fake news : brief notes on imitative artificial intelligence
    Barreto, Alana Maria Passos
    [J]. INTERNATIONAL REVIEW OF INFORMATION ETHICS, 2024, 33
  • [6] Automated and Interpretable Fake News Detection With Explainable Artificial Intelligence
    Giri, Moyank
    Eswaran, Sivaraman
    Honnavalli, Prasad
    Daniel, D.
    [J]. JOURNAL OF APPLIED SECURITY RESEARCH, 2024,
  • [7] Artificial intelligence-friend or foe in fake news campaigns
    Wecel, Krzysztof
    Sawinski, Marcin
    Strozyna, Milena
    Lewoniewski, Wlodzimierz
    Ksiezniak, Ewelina
    Stolarski, Piotr
    Abramowicz, Witold
    [J]. ECONOMICS AND BUSINESS REVIEW, 2023, 9 (02) : 41 - 70
  • [8] Application of Artificial Intelligence Techniques to Detect Fake News: A Review
    Berrondo-Otermin, Maialen
    Sarasa-Cabezuelo, Antonio
    [J]. ELECTRONICS, 2023, 12 (24)
  • [9] Certain Investigation of Fake News Detection from Facebook and Twitter Using Artificial Intelligence Approach
    Roy Setiawan
    Vidya Sagar Ponnam
    Sudhakar Sengan
    Mamoona Anam
    Chidambaram Subbiah
    Khongdet Phasinam
    Manikandan Vairaven
    Selvakumar Ponnusamy
    [J]. Wireless Personal Communications, 2022, 127 : 1737 - 1762
  • [10] Fake news detection within online social media using supervised artificial intelligence algorithms
    Ozbay, Feyza Altunbey
    Alatas, Bilal
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2020, 540