One Angry Review Can Change Thousands of Minds
Bich Ha Nguyen
Dai Nam University, Hanoi 100000, Vietnam
*Contact: hanb@dainam.edu.vn
12-06-2026
Every day, millions of people share their feelings online (Rimé, 2009). They celebrate a great restaurant experience, vent about poor customer service, or express outrage over social issues. These emotional messages may seem fleeting, but online platforms give them a remarkably long lifespan. A single review, post, or video can remain accessible for years, influencing people who were never part of the original conversation.
Researchers have long been interested in understanding how emotions expressed online affect others. Some studies focus on how emotions influence attitudes toward the object being discussed. For example, an angry review may discourage potential customers from purchasing a product, and vice versa (Yin et al., 2021; Qiu et al., 2023). Other studies examine how emotions influence reactions to the content itself, such as whether a post receives likes, shares, or comments (Berger & Milkman, 2012; Stieglitz & Dang-Xuan, 2013). Yet despite extensive research, scholars have often struggled to explain these effects consistently.
Part of the challenge lies in the theories used to study online emotions. Many explanations were originally developed for face-to-face interactions, where two individuals communicate directly with one another. Online environments operate very differently. A reviewer may never meet their audience, and readers are often more interested in the product, company, or issue being discussed than in the person expressing the emotion.
Recent research published in MIS Quarterly proposes a more comprehensive way of understanding these dynamics. Rather than assuming that emotions directly trigger reactions, the study suggests that observers interpret emotional content through multiple pathways simultaneously (Yin et al., 2026).
When reading an emotional message, people do not merely absorb the emotion itself. They also evaluate what the emotion reveals about the situation, the target being discussed, and the person expressing it. An angry review of a restaurant, for example, may signal poor service, suggest that the reviewer is highly invested in the experience, or raise questions about whether the reviewer is overreacting. These interpretations can coexist and sometimes point in different directions.
As a result, the same emotional expression can produce surprisingly different outcomes. An angry review might be perceived as less trustworthy because it seems overly emotional. At the same time, it may still persuade readers to avoid the restaurant because it highlights potential problems. Similarly, a highly emotional social media post may attract attention and sharing even when readers disagree with its message.
This perspective highlights an important reality of digital communication: emotions do not travel through online networks as simple signals. Instead, they become embedded within a complex web of interpretations shaped by personal experiences, expectations, cultural norms, and contextual cues. Different individuals may extract different meanings from the same emotional expression, leading to diverse behavioral responses (Vuong, 2025; Khuc & Nguyen, 2026).
As online platforms increasingly shape public opinion, consumer decisions, and social movements, understanding these layered processes becomes essential. The influence of emotions online is not determined solely by what people feel, but by how others interpret, filter, and connect those feelings to broader networks of meaning (Codex, 2026; Nguyen, 2026).
References
Berger, J., & Milkman, K. L. (2012). What makes online content viral?. Journal of Marketing Research, 49(2), 192-205. https://doi.org/10.1509/jmr.10.0353
Codex, A. (2026). A story of a review of a book. http://books.google.com/books/about?id=V4TiEQAAQBAJ
Khuc, V. Q., & Nguyen, M. H. (2026). Cultural Additivity Theory. Available at SSRN 6767760. https://ssrn.com/abstract=6767760
Nguyen, M.-H. (2026). Ayn Rand and Kingfisher on zero-carbon bombs and a sustainable future. Visions for Sustainability, 25(13474), 1-13. http://dx.doi.org/10.13135/2384-8677/13474
Qiu, L., Wang, W., & Pang, J. (2023). The persuasive power of emoticons in electronic word-of-mouth communication on social networking services. MIS Quarterly, 47(2), 511-534. https://doi.org/10.25300/MISQ/2022/16300
Rimé, B. (2009). Emotion elicits the social sharing of emotion: Theory and empirical review. Emotion Review, 1(1), 60-85. https://doi.org/10.1177/1754073908097189
Stieglitz, S., & Dang-Xuan, L. (2013). Emotions and information diffusion in social media—Sentiment of microblogs and sharing behavior. Journal of Management Information Systems, 29(4), 217-247. https://doi.org/10.2753/MIS0742-1222290408
Vuong, Q. H. (2025). Wild Wise Weird. AISDL. https://books.google.com/books?id=C5dDEQAAQBAJ
Yin, D., Bond, S. D., & Zhang, H. (2021). Anger in consumer reviews: Unhelpful but persuasive?. MIS Quarterly, 45(3), 1059-1086. https://doi.org/10.25300/MISQ/2021/15363
Yin, D., Bond, S. D., & Zhang, H. (2026). Tripartite Reactions to Emotions (TRE) Theory: The impact of emotional expressions in user-generated content. MIS Quarterly, 50(2), 429-462. https://doi.org/10.25300/MISQ/2025/18570
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