Abstract

This study focuses on Sina Weibo as the research platform, constructing a corpus of Traditional Chinese Medicine (TCM) marketing content spanning 2019-2024. By integrating four analytical dimensions—evaluative markers, personal pronoun features, sentiment analysis, and genre characteristics—we employ mixed quantitative and qualitative methods to investigate misinformation discourse patterns in TCM promotional posts. Key findings reveal: 1) Frequent use of intensifiers in TCM content that exaggerate therapeutic efficacy; 2) Strategic deployment of personal pronouns demonstrating persuasive tactics to enhance reader immersion and behavioral intent; 3) Dominance of positive sentiment with observable emotional manipulation tendencies; 4) Highly templatized genre structures forming deceptive logical chains through “authority + expertise + call-to-action” rhetorical moves. The research systematically identifies the prototypical discourse features of deceptive TCM marketing, aiming to provide theoretical foundations for optimizing TCM communication practices and purifying online health information ecosystems.

Keywords

Traditional Chinese Medicine (TCM), Misinformation Detection, Style, Styling

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1. Introduction

As a treasure of human civilization, traditional Chinese medicine (TCM) has played an irreplaceable role in disease prevention and health maintenance. The World Health Organization’s WHO Traditional Medicine Strategy 2014-2023 highlights that approximately 80% of the global population still relies on traditional medicine as a primary healthcare approach, with Traditional Chinese Medicine (TCM) receiving significant attention due to its unique theoretical system and clinical efficacy (World Health Organization, 2013). Cheng (2014) identified Weibo’s characteristics: information fragmentation, timeliness, explosive and contagious spread, and low information credibility. Therefore, TCM marketing texts must employ precise language strategies to attract users to stop, read, and interact within a short time. TCM promotional content leverages this platform to translate obscure traditional medical theories into accessible narratives, vividly showcasing TCM’s advantages in wellness preservation, disease prevention, and treatment. This approach not only dispels public misconceptions about TCM but also fosters emotional resonance to stimulate interest and demand, positioning itself as a pivotal vehicle for promoting TCM culture and enhancing industry influence.

However, driven by traffic-centric economic incentives, some TCM marketing content has deviated from scientific integrity. Certain accounts fabricate exaggerated efficacy claims and deceptive propaganda to maximize commercial gains, severely undermining TCM’s credibility and misleading public health decisions. This study defines “misinformation” as Traditional Chinese Medicine (TCM) marketing content that lacks scientific validation, exaggerates therapeutic efficacy, or employs rhetorical manipulation to mislead the public. The identification criteria are anchored in three authoritative dimensions: 1) conflict with regulatory frameworks, including discrepancies from the Traditional Chinese Medicine Law of the People’s Republic of China and officially issued TCM clinical guidelines; 2) reliance on unverified sources, such as non-authoritative references or fabricated expert endorsements; and 3) use of definitive claims (e.g., “complete cure,” “100% effective”) devoid of evidence-based support. Such content not only violates principles of scientific communication ethics but also poses significant risks to public health decision-making by distorting medical realities and fostering misplaced trust in unproven interventions. This urgency necessitates research on detecting potential misinformation in TCM marketing discourse. Such efforts are vital not only for purifying online information ecosystems but also for safeguarding TCM cultural heritage and public health rights. These initiatives hold profound significance for regulating TCM-related digital communication and advancing the sustainable development of TCM practices. This study systematically investigates TCM promotional content through four analytical dimensions: evaluative markers, personal pronoun features, textual sentiment, and genre characteristics.

Evaluative Markers (including intensifiers, hedges and booster, and attitude markers): Overly absolute statements and efficacy-exaggerating vocabulary serve as “red flags” for misinformation. Identifying high-frequency markers enables precise detection of deceptive tendencies.

Personal Pronoun Features (first-, second-, and third-person usage): All pronoun types may function as manipulative rhetoric. Analyzing their distribution patterns helps expose coercive persuasion tactics.

Textual Sentiment (positive/negative polarity): Misleading content often employs anxiety-inducing narratives or false promises with extreme emotional appeals. Quantifying sentiment intensity and direction reveals authenticity risks.

Genre Characteristics: Features like flawed causal logic and fragmented case compilations provide critical clues. Templates combining “authority endorsements + pseudo-specialist claims + urgent calls-to-action” form systematic deception frameworks.

Through multidimensional cross-analysis, this research establishes a comprehensive detection model for identifying misinformation in TCM marketing content. The findings aim to provide scientific foundations and technical solutions for standardizing online TCM communication and fostering a trustworthy health knowledge ecosystem.

2. Literature Review

2.1. Evaluative Markers

Appraisal theory was proposed by linguists such as James Robert Martin in the 1990s. Martin and White (2005) defined appraisal theory as “the evaluation of—that is, the various attitudes that can be negotiated in discourse, the intensity of emotions involved, and the various ways of indicating values and connecting with readers”. Evaluative discourse marker, as an important concept in appraisal theory, have been gradually clarified and studied in depth during the development of this theory. Zhang and Wu (2018) argued that appraisal theory focuses on the evaluative resources in discourse, discussing the intensity, force, and sources of various attitudes in discourse, and attempts to demonstrate how speakers express their attitudes, positions, and viewpoints in discourse through discourse analysis. While the concept of metadiscourse was initially proposed by linguist Zelling Harris, and Hyland has researched and developed it further. Hyland (2005: p. 37) defined metadiscourse as a term for self-reflective expressions used to negotiate interactive meanings in texts, helping authors express viewpoints and interact with readers as members of a specific community. Metadiscourse includes boosters, hedges, and attitude markers, all of which are evaluative. Hedges and boosters play significant roles in discourse construction. Hyland (2005) viewed hedges as a means to highlight authors’ subjectivity, provide negotiation space for recipients, and promote inter-subjectivity. Hedges are a context-specific language form. Hyland (1998) noted that boosters enable writers to make positive statements, express propositions confidently, and assert facts forcefully. Emotionally, they show solidarity with readers by emphasizing shared information, group identity, and direct connections. Xiao and Tao (2008) considered the strength of boosters as subjective, reflecting the user’s attitude. Li (2011) saw boosters as a key linguistic tool for expressing stance, helping strengthen statements, convey conviction, and persuade readers to accept arguments.

2.2. Personal Pronouns

In commercial texts, the interactional functions of personal pronouns are widely used in advertisements, corporate press releases, and other genres. Fu and Yu (2022) used meta-analysis to find that first-person narrative ads create more subjective experiences, enhance perceived interactivity, and generate more favorable attitudes and behavioral intentions than third-person narratives. Chen (2021) showed that corporate newsletters use attitude markers, self-mentions, and engagement markers to emphasize interactivity for self-promotion. Gao and Li (2017) examined pronominal perspectives in English advertisements and how they facilitate consumer purchasing behavior. Huang et al. (2023) compared pronoun use in Xiamen vs. Sydney tourism posts, finding first-person plural reflects a collective stance, while second person enables dialogic interaction. Skorczynska (2020) found first-person use in corporate releases enhances conversational tone and persuasion. Al-Subhi (2022) noted inclusive pronouns build solidarity in ads, while the second person directly engages audiences, enhancing appeal and persuasiveness. Although pronominal interaction has been widely studied, significant gaps remain in the specific context of TCM marketing texts.

2.3. Sentiment Analysis

Sentiment analysis has been widely applied in social media research. Currently, the primary approaches to text sentiment analysis include lexicon-based methods and machine learning techniques. According to Dhaoui et al. (2017), a study using the LIWC2015 lexicon and the RTextTools machine learning package tested 850 consumer review samples from 83 Facebook brand pages. This study, through learning and summarizing two text sentiment analysis methods (lexicon-based and machine learning-based), has decided to conduct a manual qualitative analysis of traditional Chinese medical texts to determine their sentiment orientation. Zhang (2019) used advanced sentiment analysis tools to examine Twitter posts related to 25 publicly traded companies on Yahoo Finance, analyzing the relationship between company stock prices and sentiment trends derived from Twitter data. This study provided valuable insights for investors seeking market information. Similarly, Păvăloaia et al. (2019) conducted sentiment analysis on various social media posts about Coca-Cola and PepsiCo, including content from Facebook, Twitter, Instagram, Pinterest, Google, and YouTube, to better understand consumer preferences.

Sentiment analysis also plays a significant role in e-commerce. Li, Qian, and Zhou (2017) applied sentiment analysis to product reviews, extracting sentiment expressions related to product attributes and assessing their positive or negative tendencies. This analysis was then used to recommend high-quality products to meet consumer needs. Liu and Kan (2018) conducted an empirical study on consumer reviews of pecans sold on Tmall, demonstrating that sentiment analysis of e-commerce reviews could help businesses establish new evaluation metrics, dynamically monitor sentiment shifts, and track overall trends in the e-commerce industry.

2.4. Genre Characteristics

Based on genre theory, the predecessors have conducted structural studies on some texts, which provides excellent references for subsequent research. Li et al. (2022) combined Bhatia’s critical genre analysis method with Kress and van’s multimodal discourse analysis method to explore the Chinese version of Douyin, the hidden short video advertisement on Douyin, and reveal how this genre is manipulated to exploit consumerism and shape consumer culture. The research contributes to a deeper understanding of less explored types of deceptive new media, as well as ways to identify covert short video ads and analyze types in the era of “new media”. Herck et al. (2022) analyzed the unique integration of interpersonal strategies and transaction strategies in English emails responding to customer complaints in a B2C environment through verbal steps, revealed the importance of email in service recovery, and provided suggestions for customer service agents.

Another important social media platform, Weibo, has shown unique advantages in the field of marketing. Guo (2018) pointed out that according to the 2017 Weibo User Development Report of Sina Weibo Data Center, as of September 2017, the number of monthly active users of Weibo was 376 million, far exceeding the former king of Twitter. The huge user base and the resulting economies of scale are the innate advantages of Weibo marketing. These previous studies on business discourse and social media platforms provide excellent references for this study. At the same time, this study also makes up for the gaps in the research on the structure and linguistic features of TCM marketing advertorials, which is conducive to promoting the healthy transmission and inheritance of TCM and maintaining the image of TCM.

3. Research Methodology

3.1. Research Questions

Guided by the core objective of “Research and Development on the Detection of Potential Misinformation Discourse in TCM Marketing Accounts,” this study integrates multidimensional linguistic feature analysis to propose the following research questions:

RQ1: What are the frequency and distribution patterns of evaluative markers (boosters, hedges, and attitude markers) in TCM promotional content? Can their overly absolute or exaggerated expressions serve as reliable indicators for misinformation detection?

RQ2: How do the usage patterns and interactive strategies of personal pronouns (first-, second-, and third-person) correlate with persuasive tactics in deceptive TCM marketing?

RQ3: Do deceptive TCM promotional texts exhibit statistically significant anomalies in textual sentiment (extreme positivity/negativity)?

RQ4: Does misinformation systematically employ genre-specific rhetorical moves to construct misleading logical frameworks?

Addressing these questions will provide theoretical and empirical foundations for developing a multidimensional misinformation detection model.

3.2. Research Design

This study employs a mixed-methods research design, integrating quantitative and qualitative approaches to systematically investigate the linguistic features of TCM promotional content and their associations with misinformation. Quantitative analysis was conducted to uncover statistical patterns of linguistic markers, while qualitative analysis focused on interpreting the underlying discursive strategies embedded in deceptive texts. The research comprises three sequential phases: first, a Python-based web crawler was deployed to dynamically collect TCM marketing texts published on Weibo between 2019 and 2024, establishing an initial corpus; second, a three-stage data curation protocol involving automated deduplication, topic filtering, and manual verification was implemented to refine the dataset, resulting in 7908 high-quality samples; finally, cross-dimensional analysis integrating evaluative markers, personal pronouns, sentiment analysis, and genre characteristics was performed using AntConc corpus tools and manual annotation. This triangulated methodology ensures robust theoretical and empirical support for developing a multidimensional misinformation detection framework.

3.3. Data Collection

3.3.1. Data Sources

The research data were collected from TCM-related promotional posts published on Sina Weibo between 2019 and 2024, covering topics such as product advertisements, therapy recommendations, and wellness knowledge dissemination. To ensure data diversity and temporal relevance, a Python-based dynamic crawler was developed with 45 predefined search keywords, including “Traditional Chinese Medicine,” “acupuncture,” “wellness,” and “remarkable efficacy.” The crawling process incorporated a sensitive term filtration system to exclude high-risk phrases (e.g., “cancer,” “discount”) and employed a dynamic time-interval algorithm (1 - 5 days) to mimic human browsing patterns, thereby avoiding platform detection mechanisms. A total of 50,000 raw texts were initially harvested, forming the foundation for subsequent analysis.

3.3.2. Sample Selection

To enhance data representativeness and validity, a rigorous three-stage filtering protocol was implemented. First, automated preprocessing removed duplicate entries and non-textual elements such as hyperlinks, videos, and advertisements. Second, topic-based filtering excluded non-promotional content, including scientific articles and news reports. Finally, manual verification was conducted by two independent annotators to eliminate ambiguous or non-persuasive texts, ensuring the retained samples were strictly aligned with the characteristics of marketing discourse. After this curation process, 7908 valid texts were retained, with 100 randomly selected as the core analytical sample to balance depth and feasibility.

3.4. Data Analysis

Quantitative Analysis

Quantitative analysis was conducted using Excel and AntConc corpus tools to systematically examine linguistic patterns across four dimensions. For evaluative markers, frequency distributions of intensifiers (e.g., “彻底” [thoroughly], “绝对” [absolutely]), hedges (e.g., “可能” [possibly], “适量” [moderately]), and attitude markers (e.g., “震惊” [astonishing], “奇迹” [miracle]) were calculated to identify exaggerated or absolutist language. Personal pronoun usage was analyzed by quantifying the ratios of first-person (我/我们 [I/we]), second-person (你/你们 [you]), and third-person (他/他们 [he/they]) references to uncovering persuasive tactics. Sentiment analysis involved annotating extreme positive claims (e.g., “百分百有效” [100% effective]) and negative fear appeals (e.g., “致命风险” [fatal risk]) based on a predefined sentiment lexicon, followed by statistical profiling of emotional intensity. Genre features were assessed through frequency counts of rhetorical moves, including authority endorsements (e.g., “专家推荐” [expert-recommended]), pseudo-specialist explanations, and urgent calls-to-action, to detect systematic deceptive frameworks.

4. Research Findings and Discussion

4.1. Research Findings

Through quantitative analysis of evaluative markers, personal pronoun features, textual sentiment, and genre characteristics in TCM marketing posts, the study reveals the following key findings, as summarized in Table 1.

Table 1. Frequency and distribution of evaluative markers.

The analysis reveals that evaluative markers—comprising boosters, hedges, and attitude markers—were identified 127 times in the sample. A detailed breakdown shows that boosters occurred most frequently (67 instances, 52.76%), indicating that marketers tend to employ boosters to amplify perceived advantages of products or services, thereby highlighting critical information to capture consumer attention. Hedges appeared 41 times (32.28%), while attitude markers were the least frequent (19 instances, 14.96%). The relatively lower frequency of hedges may stem from marketers’ concerns that such language could diminish persuasive efficacy by introducing uncertainty, potentially undermining consumer trust and purchase decisions. Similarly, the scarcity of attitude markers might reflect strategic avoidance of overtly subjective expressions in TCM promotional content, as excessive emotional appeals could trigger consumer skepticism. Instead, these texts prioritize an objective and professional tone to reinforce credibility.

The statistical results reveal in Table 2 that within the research corpus (N = 100), comprising 32,400 words, strategic personal pronouns were deployed 510 times. First-person singular pronouns (“我” [I]) exhibited the highest frequency (45.7%), suggesting authors frequently leverage personal narratives to enhance credibility. Second-person singular pronouns (“你” [you]) accounted for 29.2% of usage, reflecting a deliberate strategy to engage readers through direct address and awaken perceived needs. First-person plural pronouns (“我们” [we]) occurred 73 times, while third-person singular pronouns (“他/她” [he/she]) appeared 48 times. In contrast, second- and third-person plural pronouns (“你们” [you-plural], “他们” [they]) showed markedly lower frequencies, potentially indicating authors’ limited utilization of collective identity appeals to establish group affiliation.

Table 2. The frequency and proportion of personal pronouns.

As demonstrated in Table 3, the findings demonstrate a predominance of positive sentiment (73%) in TCM promotional content, primarily driven by the strategic use of persuasive language emphasizing therapeutic efficacy, leveraging endorsements from authoritative institutions or experts to bolster public trust, and employing psychological priming techniques to facilitate content dissemination. In contrast, negative sentiment accounted for 27% of analyzed posts, stemming predominantly from skepticism toward TCM’s effectiveness and safety, as well as dissatisfaction with personal treatment experiences.

Table 3. Sentiment analysis of traditional Chinese medical texts.

As demonstrated in Table 4, the frequency distribution of rhetorical moves reveals distinct patterns in the analyzed TCM marketing posts (N = 100). Authority endorsement appears in 67% of cases, with 50% attributed to usernames claiming medical credentials and 26% involving self-presentation as practitioners. Topic framing (47%) and professional explanations (91%) dominate the discourse, with the latter subdivided into disease knowledge explanations (77%) and prescription recommendations (65%). Narrative persuasion (30%) and calls-to-action (80%) further complete the rhetorical framework.

Table 4. The move/step, frequency of occurrence.

The data indicates that professional explanations are the most prevalent rhetorical move, followed closely by calls-to-action, underscoring two core functions of TCM promotional content: establishing professional credibility through authoritative claims and fostering reader engagement through interactive directives. These texts strategically reinforce TCM’s expertise via authority endorsement, topic framing, and technical elaboration to cultivate trust, while simultaneously embedding mechanisms (e.g., urgency-driven calls-to-action) to guide consumer behavior. By systematically intertwining expertise narratives with participatory prompts, such discourse aims to convert potential readers into active consumers.

4.2. Discussion

To comprehensively understand the functional roles of evaluative markers, personal pronouns, textual sentiment, and genre features in TCM marketing posts on Weibo, qualitative analysis was employed to explore the underlying motivations behind authors’ discursive strategies across these dimensions.

The predominance of boosters (67 instances, 52.76%) over hedges (41 instances, 32.28%) and attitude markers (19 instances, 14.96%) highlights a deliberate emphasis on exaggerated claims. When skillfully integrated, evaluative markers enhance user engagement and stimulate discussions. However, their misuse—particularly the hyperbolic deployment of boosters to inflate product efficacy beyond realistic outcomes—creates unrealistic consumer expectations, ultimately eroding trust in TCM when results fall short. Similarly, hedges are weaponized by unethical marketers to evade accountability through ambiguous language, while attitude markers exploit emotional appeals lacking factual grounding, leading to consumer disillusionment post-purchase. Collectively, these practices disrupt TCM’s market integrity and hinder its sustainable development.

The high frequency of first-person singular pronouns (e.g., “我” [I]) reflects strategies to bolster authority through personalized expertise narratives. First-person plural pronouns (“我们” [we]) blur author-reader boundaries, fostering a false sense of shared interests to reduce reader skepticism. Second-person singular pronouns (“你” [you]) dominate interactive engagement, directly invoking health anxiety or empathy to trigger behavioral responses. While second-/third-person plural pronouns are less frequent, they subtly induce collective health concerns or imply universal product benefits. Third-person singular pronouns (“他/她” [he/she]) validate efficacy indirectly through case studies, circumventing overt promotional resistance. This pronoun orchestration constructs a persuasive chain, yet its ethical dilemma lies in masking commercial agendas as “genuine care,” thereby suppressing public critical awareness.

Positive sentiment dominates (76.47%), driven by persuasive language emphasizing therapeutic efficacy, authoritative endorsements, and psychological priming techniques. Extreme positive claims (e.g., “instant results” or “cure-all”) amplify public confidence but risk distorting medical realities, particularly in fragmented social media ecosystems where unverified assertions spread rapidly. Negative sentiment (23.53%) stems from skepticism toward TCM’s safety/efficacy and dissatisfaction with personal treatment outcomes. Though less prevalent, negative posts often resonate more deeply, using emotionally charged language (e.g., “no improvement” or “wasted money”) to reflect disappointment. Such sentiment polarizes public attitudes, potentially fueling broader debates about TCM’s scientific validity, especially when influenced by subjective biases or external narratives.

TCM marketing posts exhibit deliberate genre structuring to balance persuasion and subtlety. Authority endorsement (67%), topic framing (47%), professional explanations (91%), narrative persuasion (30%), and calls-to-action (80%) synergistically construct a “credibility-to-conversion” pipeline. Authors first establish medical authority through technical discourse and case studies, then deploy urgent directives (e.g., “limited-time offers”) to catalyze consumer action. This genre hybridity masks commercial intent under a veneer of expertise, enabling marketers to manipulate reader attitudes while minimizing resistance.

While this study focuses on Weibo, the applicability of its findings to closed-network platforms like WeChat requires further validation. Preliminary observations indicate that WeChat posts, influenced by private traffic dynamics, predominantly employ acquaintance-endorsed narratives (e.g., “recommended by friends”), whereas Weibo content relies more on constructing authoritative expertise personas (e.g., “TCM master with 30 years of experience”). These platform-specific disparities suggest that deceptive tactics may adapt to distinct audience engagement mechanisms. Future research should expand cross-platform comparative analyses to refine detection models’ generalizability, particularly in addressing context-dependent rhetorical strategies across open and closed social ecosystems.

5. Conclusion

This study systematically investigates the linguistic composition and dissemination mechanisms of deceptive discourse in TCM marketing through a multidimensional analytical framework. Key findings reveal that misleading content strategically employs boosters to exaggerate efficacy, pronoun-driven persuasion to simulate trust, polarized sentiment to bypass rational judgment, and genre templating to fabricate credibility. While these tactics effectively cultivate professional personas and stimulate consumer behavior, their inherent deceptiveness exacerbates public distrust in TCM.

The research validates the efficacy of discourse-based detection models, offering actionable insights for regulators, social platforms, and health communicators to identify and mitigate misinformation. To counter misinformation in TCM marketing, platforms should deploy automated early-warning systems leveraging multidimensional linguistic features (e.g., frequent boosters, polarized sentiment, templated structures) to flag and throttle high-risk accounts. Regulatory bodies must establish TCM content guidelines mandating evidence-based citations for efficacy claims and prohibiting deceptive phrases like “absolute cure.” Concurrently, collaborative efforts with medical institutions should advance media literacy initiatives, empowering the public to identify manipulative discourse patterns such as “authority endorsement + urgent calls-to-action.” These integrated measures—technological governance, policy enforcement, and public education—form a tripartite strategy to safeguard both TCM’s cultural integrity and public health ecosystems. By advancing detection capabilities across diverse content types, this research aims to foster a trustworthy digital ecosystem for TCM communication, safeguarding both cultural heritage and public health.

Acknowledgements

We would like to express our gratitude to the predecessors who have worked diligently in the academic field. Your research achievements have laid a solid foundation for our thesis. The light of your wisdom has illuminated our path of exploration. This thesis embodies the efforts and assistance of countless people. We are grateful to have had your company along the way, and we will continue to forge ahead on the academic path with this gratitude. We are also grateful to Weibo, a social media platform with abundant data, which served as the primary data source for our research.

Funding

This research was supported by the College Students’ Innovation and Entrepreneurship Training Program of Sichuan University of Arts & Science, Project No: S202410644083.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References