Information Manipulation Through a Linguistic Anthropological Lens

Joanne Lee
Vanderbilt University

Abstract

The modern-day attention economy can be described with a singular quote by Herbert Simon (1916–2001), which reads, “In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes” (1971, as cited in Ratcliffe, 2017). As highlighted by Simon, our ability as humans to critically analyze information and recognize validity across false statements diminishes when faced with an increased flow of information, making us subject to various forms of information manipulation. In the realm of communication and media, information manipulation can occur in the forms of misinformation, mal-information, and disinformation—each of which is discerned based on the accuracy, intent, and context behind the information being shared. In this essay, I will draw on linguistic anthropology to define the three types of information manipulation and outline the theoretical framework that will underpin the subsequent analyses. I will then provide an example of each type of information manipulation, namely, Kim Iversen’s misinformation during the COVID-19 pandemic, Donald Trump’s mal-information during his 2024 presidential campaign, and Volkswagen’s disinformation regarding their clean diesel technology, and analyze each example’s production, circulation, consumption, and impact through examining the role of framing and discourse. Then, drawing on these analyses, I will discuss the concepts of why people share fake news, the third-person effect, and its contributions toward audience vulnerability. Finally, I will conclude by proposing ways in which a linguistic anthropological perspective could help individuals effectively navigate the three variations of information manipulation across rapidly evolving media environments.

Definitions

As mentioned previously, manipulative information can be divided into three distinct categories—misinformation, mal-information, and disinformation. Misinformation can be recognized as false information shared without the intent to deceive. It is a reflection of how trusting particular linguistic forms, for example, scientific jargon or authoritative speech, can cause those within such speech communities to accept certain claims without skepticism. Oftentimes, misinformation can be pervasive and can appear to be harmless when it is not, thus, threatening the safety or well-being of individuals. Mal-information is true information shared with the intent to deceive. This type of information manipulation works with framing to display false information as truth by capitalizing on contextual sociocultural norms. Disinformation is false information shared deliberately with the intent to deceive. Disinformation often involves leveraging linguistic hegemony, or the dominance of a particular language or linguistic standard, to normalize dominant ideologies and reinforce in-group biases— the tendency to favor one’s own group over others.

Misinformation

A notable period of misinformation emerged during the COVID-19 pandemic, to the extent that the concept of “COVID-19 misinformation” became a widespread phenomenon. An example of misinformation during this period was a tweet by Kim Iversen, who tweeted, “MASSIVE peer reviewed study of Ivermectin concludes regular use as a prophylactic agent was associated with significantly reduced COVID-19 infection, hospitalization, and mortality rates,” with an attachment of a peer-reviewed study (Iversen, 2022). This tweet is identified as misinformation, as it presents misleading information without malicious intent. The study in the tweet was distorted and exaggerated its findings to challenge broader consensus from scientific communities, such as the World Health Organization (WHO) and U.S. Food and Drug Administration (FDA), who concluded there was a lack of evidence supporting Ivermectin as a remedy or preventive measure against COVID-19.

Kim Iversen, the producer of this tweet, leveraged the credibility associated with scientific research articles to project an image of authority. To further amplify persuasion, the tweet utilized emotionally charged phrasing—such as “MASSIVE” and “significantly”—to create an intense sense of urgency, emphasizing the significance of the claim. Such linguistic tools led to the information being framed in ways that minimized urges for critical evaluation and maximized emotional reactions across speech communities already predisposed to skepticism around vaccines. Despite the “peer-reviewed” nature of the study, the exaggerated conclusions misled audience members about its true findings.

The rapid spread of this misinformation was driven primarily by the amplifying mechanisms on the social media platform, Twitter, where the tweet was first uploaded. The first mechanism points to the algorithm, which ensured that exaggerated assertions similar to those of Iversen were given precedence over alternative posts due to their high engagement from likes, comments, and retweets. As mentioned previously, the tweet was also shared in echo chambers that already had skepticism toward vaccines or were seeking substitutive COVID-19 treatments, leading to rapid sharing among peers and reinforcing existing ideologies. The spread of this misinformation relates to Gumperz’s (2001) framework on speech communities, where he notes, “The speech varieties employed within a speech community form a system because they are related to a shared set of social norms (Gumperz, 2001, p. 44). Echo chambers on social media platforms function as speech communities and reinforce confirmation biases by circulating tweets among networks where alternative medical approaches are trusted.

Many consumers of Iversen’s misinformation had already demonstrated doubt toward mainstream medical guidance or had been searching for a different approach to treating COVID-10. The majority of such individuals lacked the necessary critical evaluation skills to further dissect and scrutinize claims established in the tweet, making them further inclined to accept the misinformation as truth due to existing confirmation biases. Attaching a scientific study enhances credibility, skews viewers’ perceptions of claims, and reinforces pre-existing ideologies. Furthermore, according to Akkaya (2014), “it is social actors/performers who mediate and negotiate (deploy and play with) various ideologies and semiotic resources in a given discursive encounter to accomplish artful performances” (p. 285). Kim Iversen’s role as a social actor, given her 223.1 thousand followers, inevitably allowed her personal opinions to influence perceptions and potentially cause complications among her consumers if she had not intended such outcomes.

The result of the misinformation’s spread had various severe impacts. With respect to public health, those who believed Iversen’s tweet established false confidence in the abilities of Ivermectin and opted for such measures to prevent COVID-19 over scientifically backed options such as vaccines. These actions not only left individuals exposed to a higher risk of COVID-19 but also strained healthcare systems, as the misuse of these drugs raised poisoning cases and contributed to inefficient allocation of medical resources. Socially speaking, the misinformation deepened political divides between advocates of mainstream COVID-19 guidelines and those supporting alternative treatments. It also decreased trust among healthcare officials and science-based research, intensifying public skepticism and attitudes toward institutions. Although Ivermectin’s validity as a treatment was later debunked, the misinformation continued to shape public opinion through continued circulation, highlighting the challenges of countering misinformation after it gains traction.

Mal-Information

Mal-information is seen in an anti-Harris ad created as a part of President Donald Trump’s campaign, where it showcased a quote, “Harris is seeking to significantly raise taxes,” crediting The New York Times (Trump, 2024). Although this is true, it is only true in part due to the lack of context. In the original article, the New York Times wrote, “No one making less than $400,000 a year would see their taxes go up under the plan. Instead, Ms. Harris is seeking to significantly raise taxes on the wealthiest Americans and large corporations” (Duehren, 2024). The ad took a truncated line from the article and made it seem as though Harris was seeking “to significantly raise taxes” on all Americans, when this was not inherently true, making this an example of mal-information.

This ad intentionally leveraged such vague language in its production to lead viewers to assume a broader tax increase compared to what Harris proposed. The choice of a credible source such as the New York Times, one that often faces criticism by conservatives, boosts credibility across doubtful audience members. By truncating Harris’s tax policy and leaving out crucial context, the ad framed Harris as a threat to individual finances and influenced their perception of her as a candidate. This aligns with the linguistic anthropological concept of framing, defined by Harvey (2023) as promoting a “particular definition, causal interpretation, moral evaluation and/or treatment recommendation” (p. 2).

The ad was distributed across both traditional and digital media platforms, ranging from television to social media platforms such as X (formerly Twitter), Instagram, and Facebook, where algorithms tend to push divisive content across feeds. Furthermore, it was distributed across Trump’s campaign websites and newsletters for direct access from Trump’s core supporters and amplified through sharing of the ad among Trump supporters, media coverage by both liberal and conservative outlets, and echo chambers within conservative media communities—further pushing the message in like-minded viewers. As highlighted by Heiss et al. (2023), “literacy could counteract the influence of echo chambers,” suggesting that an audience with greater social media literacy may have questioned the selective framing exhibited in the ad. However, even such literate individuals may have been impacted by Trump’s role as a social actor. His influential position and former presidential role mirrors Akkaya’s (2014) observation that individuals who are deemed as “social actors” negotiate ideological standpoints to achieve their goals, in this case, the presidency.

The ad targeted swing voters who were concerned about economic policies regarding income and taxes as well as Trump’s central supporters who have a tendency to distrust Harris. Across these consumers, the ad likely shaped perceptions of Harris as a financial risk while pushing a negative image with regards to Harris onto existing Trump supporters. Moreover, such striking and eye-catching statements likely leveraged concepts such as “clickbait,” as described by Marwick and Lewis (2017), where “The media’s dependence on social media, analytics and metrics, sensationalism, novelty over newsworthiness, and clickbait makes them vulnerable to such media manipulation” (p. 1).

As a result, the malinformation of the ad damaged Harris’s credibility, causing emotional manipulation by stirring up anxieties about financial stability from raised taxes. Most importantly, the ad mobilized voter support—reinforcing loyalty and donations across the Trump base, swaying undecided voters, and influencing the outcomes of a nationwide presidential election.

Disinformation

Disinformation is evident in a commercial advertisement by Volkswagen, known as their “Three Old Wives Talk Dirty” TV spot (Volkswagen, 2009). The ad featured a group of three elderly women who communicated their opinions about diesel technology, which were later contrasted through the ad’s promotion of “Volkswagen’s clean diesel technology,” emphasizing the environmental friendliness of the TDI cars. The truth, however, was that these claims were a facade. Volkswagen was entangled in an emissions testing scandal where it was discovered that they falsified emissions data, with actual emissions far exceeding the levels that had been reported (Federal Trade Commission, 2016).

Volkswagen’s ad was designed to attract eco-friendly and sustainable living customers by marketing their products as greener alternatives over traditional gasoline engine cars. Featuring three elderly women discussing the benefits of “clean diesel,” the company harnessed humor and relatability and established an engaging message that masked potential dishonesty in the campaign.

The misleading ad was circulated through both traditional and digital media platforms. Volkswagen's advertisement first aired on television broadcasts but was also later uploaded on platforms such as YouTube and referenced in online campaigns. Volkswagen’s public image as a reliable and well-established company further led customers to give the company more credibility and made claims of “clean diesel” more convincing. Again, this ties back to Akkaya’s (2014) claim that social actors mediate ideologies and manipulate available resources to achieve credibility. With a history of established brand trust, Volkswagen allowed its claims to resonate among members of the intended audience.

This campaign targeted consumption toward eco-conscious customers with high inclinations to purchase sustainable products but was consumed by all members regardless of their environmental outlook. Through television broadcasts, the commercial was able to reach a broad variety of customers—from families and professionals to retired individuals who expressed more concern toward sustainable purchasing decisions.

The impact of the disinformation from the ad had a multitude of consequences. On the consumer side, the false information led to misguided purchases and led customers to believe they were making an environmentally friendly choice when, in truth, they were contributing to greater environmental harm. In a world where climate change is a pressing issue, efforts such as these hinder international sustainability goals and undermine global sustainability efforts. From a broader perspective, Volkswagen's advertisements led to public distrust in corporate sustainability claims and cast doubt on the validity of similar environmentally friendly commitments by companies in the wider industry.

Fake News, The Third Person Effect, and Audience Vulnerability

Based on the examples above, it is only natural to question the incentives behind why individuals are inclined to share fake news. Fake news spreads across digitally influenced bubbles, where sharing within and across social media platforms is incentivized through cognitive and emotional aspects. As illustrated by Talwar et al. (2019), “online trust, self-disclosure, fear of missing out (FoMO), and social media fatigue are positively associated with the sharing fake news (intentionally)…online trust has negative association with authenticating news before sharing” (p. 72). Take, for example, the case of Iversen's tweet of misinformation. Her message contained emotionally charged phrases and convincing scientific jargon which stirred emotional reactions to make her arguments convincing. Resonating with communities opposing mainstream medical guidance, such information was likely shared rapidly among the affected echo chambers and facilitated by the seamless sharing features across digital platforms.

Furthermore, it is important to understand the influence of the third-person effect in raising susceptibility to false and manipulative information. To lay the framework, the third-person effect refers to the psychological phenomenon where individuals believe messages on mass media have a larger influence on others than themselves. As stated by Lev-On (2017), “Facebook users believe themselves to be less vulnerable than others to risks related to Facebook use,” illustrating the dangers of the third-person effect (p. 258). This perceived immunity decreases self-awareness and inclinations to critically evaluate information individuals encounter, leading to increased vulnerability towards information manipulation. The third-person effect is a phenomenon applied to platforms beyond just Facebook and digital social media platforms. For example, in the Volkswagen disinformation case study, the company was able to greenwash its audience members by exploiting the weak points of viewers, namely, their overconfidence in their capacity to discern truth from deceit.

Taken together, these factors reveal the ways emotional and cognitive liabilities across individuals not only fuel the spread of fake news but also increase viewer susceptibility toward misinformation, mal-information, and disinformation.

Navigating Manipulative Content Through Linguistic Anthropology

Given the ever-changing media environments, it is important to have a toolkit of strategies to navigate and mitigate the vulnerability of falling prey to information manipulation. Linguistic anthropology provides many mechanisms to go about this on a daily basis. One key suggestion is to develop an understanding of the framing and structuring of messages to identify and recognize malicious intent. For example, emotionally charged language, as exhibited by Iverson’s tweet or the purposeful omission of context seen in Trump’s anti-Harris ad, could be identified through careful dissection of message framing. Developing skills to examine emotional tone, language choice, and missing context can help individuals navigate deception. Another way to utilize concepts of linguistic anthropology is to hone the skill of recognizing norms of speech communities. Speech communities play a large role in sharing information and establishing trust, for example, the Volkswagen advertisement appealed to environmentally conscious customers, while Trump’s malinformation appealed to conservative communities. When individuals reflect on the shared norms within the speech communities they identify with, it can be easier to shift through manipulative content and challenge possible echo chambers. A final way to leverage linguistic anthropology is to understand the role of power dynamics in shaping language. The case studies exhibited concrete examples of authoritative figures manipulating information due to their credible status and large following. When audience members understand the role of power dynamics, they can evaluate and scrutinize claims that overlap seamlessly with primary ideologies and reduce susceptibility from influencers or political actors. Through these approaches, namely, analyzing framing, reflecting on speech communities, and exhibiting awareness of power dynamics, individuals can use a linguistic anthropological framework to guide their interactions with information across fast-changing environments.

References

Akkaya, A. (2014). Language, discourse, and new media: A linguistic anthropological perspective. Language and Linguistics Compass, 7. 285-300.

Duehren, A. (2024, August 22). What we know about Kamala Harris’s $5 trillion tax plan so far. The New York Times. https://www.nytimes.com/2024/08/22/us/politics/kamala-harris-tax-plan.html

Federal Trade Commission. (2016, March 29). FTC charges Volkswagen deceived consumers with its “clean diesel” campaign. https://www.ftc.gov/news-events/news/press-releases/2016/03/ftc-charges-volkswagen-deceived-consumers-its-clean-diesel-campaign

Gumperz, J. J. (2001). Speech community. In A. Duranti (Ed.), Linguistic anthropology: A reader (pp. 43–53). Blackwell Publishing.

Harvey, T. S. (2023). COVID-19, framing and naming a pandemic: How what is not in a disease name may be more important than what is. Pathogens, 12(2), 346. https://doi.org/10.3390/pathogens12020346

Heiss, R., Nanz, A., & Matthes, J. (2023). Social media information literacy: Conceptualization and associations with information overload, news avoidance and conspiracy mentality. Computers in Human Behavior, 148. https://doi.org/10.1016/j.chb.2023.107908

Iversen, K. [@KimIversenShow]. (2022, March 9). MASSIVE peer-reviewed study of Ivermectin concludes regular use as a prophylactic agent was associated with significantly reduced COVID-19 infection, hospitalization, and mortality rates. [Tweet]. X. https://x.com/KimIversenShow/status/1501267842376908800

Lev-On, A. (2017). The third-person effect on Facebook: The significance of perceived proficiency. Telematics and Informatics, 34(4), 252-260.

Marwick, A., & Lewis, R. (2017). Media manipulation and disinformation online. Data & Society Research Institute. https://datasociety.net/library/media-manipulation-and-disinfo-online/

Ratcliffe, S. (Ed.). (2017). Oxford essential quotations (5th ed.). Oxford University Press. https://doi.org/10.1093/acref/9780191843730.001.0001

Talwar, S., Dhir, A., Kaur, P., Zafar, N., & Alrasheedy, M. (2019). Why do people share fake news? Associations between the dark side of social media use and fake news sharing behavior. Journal of retailing and consumer services, 51, 72-82.

Trump, D. J. [@realDonaldTrump]. (2024, October 24). [Tweet]. X. https://x.com/realDonaldTrump/status/1850387415199842485

Volkswagen. (2009, April 22). Volkswagen Golf TDI Old Wives Clean Diesel commercial [Video]. YouTube. https://www.youtube.com/watch?v=pDI0jFZRnLU

---

Scaffold: A Showcase of Vanderbilt First-Year Writing, Volume 7, Spring 2025

Scaffold is a digital collection of first-year writing curated by the Vanderbilt Writing Studio. To highlight the developing writing processes and learning experiences central to the growth of new college writers, the collection pairs each piece with a recorded reflection from its author. Visit Scaffold’s website to listen to the authors reflect, to learn more, and to tap into this collection as a resource for college students and instructors alike.

The copyright to this work rests with the author. Proper attribution required. Vanderbilt retains a non-exclusive right to distribute the work as part of this collection.