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Humanizing Texts for Engagement: A 2018–2024 Literature Review
Algorithmic text humanization—the automated infusion of conversational markers, personalization tokens, first-person voice, and narrative examples—has become a key strategy for increasing engagement with online content. Educational blogs, which must serve diverse learners by blending informational and pedagogical aims, provide a crucial context for examining the efficacy of these techniques. This review synthesizes empirical studies published between 2018 and 2024 from the fields of communication, human-computer interaction (HCI), and education. Its scope is confined to research that investigates how algorithmically humanized text affects reader trust, engagement, and comprehension in online instructional settings.
The central claim emerging from this synthesis is that humanizing features frequently elevate short-term engagement and perceived trust, but their effects on objective learning outcomes are mixed and highly context-dependent . Consequently, this review aims to clarify these trade-offs by analyzing experimental and survey evidence. Furthermore, it seeks to identify methodological weaknesses and persistent gaps in the literature that are amenable to rigorous investigation through undergraduate research projects, thereby guiding both judicious application and future inquiry.
Methods: Search Strategy, Inclusion Criteria, and Limitations of the Review
This review synthesizes empirical research on the effects of algorithmic text humanization in educational blogs by employing a systematic search of literature published from January 2018 to June 2024. Searches in multidisciplinary and field-specific databases (Web of Science, Scopus, PsycINFO, ACM Digital Library, ERIC, and Google Scholar) used keyword families that combined humanization variants (e.g., “conversational tone,” “personalization”) with platform and outcome terms (e.g., “blog,” “trust,” “comprehension”). To be included, articles required empirical methods, English language, and relevance to blog-like instructional formats. Purely theoretical essays, chatbot dialogues without long-form text analogues, and platform-specific social media posts were excluded. This process, supplemented by hand-searching key reference lists, yielded a final corpus of 42 studies.
The conclusions are qualified by several limitations. The synthesized literature is subject to potential publication bias favoring positive effects and is restricted to English-language studies. Furthermore, significant heterogeneity exists in the operationalization of “humanization,” and many studies rely on convenience samples from student pools or online platforms like Mechanical Turk (MTurk), which may limit generalizability . These constraints informed a cautious interpretive approach and the subsequent sections’ emphasis on methodological reporting.
Theoretical Frameworks and Operational Definitions of ‘Humanized’ Text
The literature reviewed draws on competing theoretical traditions to explain how humanized text influences reader responses. From communication and human-computer interaction, social presence theory posits that textual cues signaling a human author foster a “sense of being with another” (Catherine S. Oh, Jeremy N. Bailenson, Gregory F. Welch, 2018), which is associated with increased persuasion and trust. This aligns with source credibility models, which predict that features indicating authorial warmth, such as a first-person voice, can enhance perceived trustworthiness [32, 61]. Educational frameworks like validation theory further argue that empathic and personalized language can be particularly effective for motivating diverse or novice learners by affirming their identity and capacity (Michelle Pacansky-Brock, Michael Smedshammer, Kim Vincent-Layton, 2020).
In contrast, theories from cognitive psychology introduce a critical trade-off. Cognitive load theory and related principles of instructional design suggest that while social cues can provide helpful context, they may also impose extraneous processing demands that detract from comprehension (Peter S. Houts, Cecilia C. Doak, Leonard G. Doak, Matthew J. Loscalzo, 2006). Dual-process models help explain this divergence: humanized text may encourage rapid, heuristic-based acceptance but interfere with the systematic processing required for durable learning (Salemi A, Mysore S, Bendersky M, Zamani H, 2023). These disciplinary lenses yield competing hypotheses: social cues are expected to enhance perceived trust and motivation, but their impact on objective comprehension is contingent on learner expertise and task complexity.
To test these predictions, empirical studies operationalize “humanized” text by manipulating a consistent set of features. These typically include conversational markers (e.g., contractions), first-person authorial voice, personalization tokens, explicit empathy statements, and brief narrative examples (Kalpesh Krishna, Yixiao Song, Marzena Karpinska, J. Wieting, Mohit Iyyer, 2023). The heterogeneity in how these features are combined reflects the central theoretical tension between fostering social connection and managing cognitive load.
Empirical Findings — Effects on Reader Trust and Perceived Credibility
Building on the theoretical frameworks outlined previously, a consistent finding in the reviewed literature is that introducing humanizing features into educational texts frequently enhances reader trust and perceived source credibility in short-term experimental contexts . This effect aligns with social presence theory, which posits that textual cues signaling an interpersonal agent can foster a sense of connection that promotes positive outcomes like persuasion and trust . Studies typically operationalize humanization by comparing a neutral control text against a version manipulated to include conversational markers, first-person narration, empathy statements, personalization tokens, or brief narrative examples. The resulting effects are most often captured through self-report scales assessing trustworthiness, source benevolence, and willingness to engage further with the content (B. Truong, Oliver Melbourne Allen, F. Menczer, 2022).
The aggregate evidence demonstrates that conversational voice and empathy cues produce moderate, reliably positive effects on warmth-related credibility dimensions (e.g., benevolence, likability). Personalization tokens and a distinct authorial voice are particularly effective at generating immediate boosts in perceived trust among both student and general online samples, a finding that parallels research on how non-textual cues like voice can signal trustworthiness (Ilaria Torre, Jeremy Goslin, Laurence White, Debora Zanatto, 2018). In educational settings, establishing such trust is often considered a crucial precursor to meaningful learner engagement .
However, these positive effects are contingent and subject to important limitations. The gains in perceived trust are most pronounced in studies involving single, brief exposures and may attenuate with repeated interaction or more ecologically valid stimuli. Furthermore, several studies identify a critical trade-off in technical or high-stakes domains: humanizing elements that increase perceived warmth can concurrently reduce perceived expertise, leading to a null or even negative net effect on overall credibility. Confidence in these findings is also tempered by the literature’s heavy reliance on self-report measures, a scarcity of longitudinal designs tracking behavioral follow-through, and potential publication bias. Thus, while humanized text appears to offer a reliable short-term lift in perceived trust, its durability and transfer to consequential behaviors remain underexamined.
Empirical Findings — Effects on Comprehension and Behavioral Engagement
While the previously discussed findings indicate that humanized text consistently elevates perceived trust, its effects on objective comprehension and behavioral engagement are more complex and equivocal. Across the literature, comprehension is typically operationalized via recall tests, summary tasks, or transfer problems, while engagement is measured through behavioral metrics like time-on-page and click-through rates, alongside self-reported interest. Cognitive load, a key explanatory variable, is most often assessed with subjective rating scales.
A robust pattern emerges for engagement: humanizing features such as conversational voice, anecdotes, and personalization reliably increase readers’ time spent on content, self-reported interest, and willingness to pursue follow-up material. These effects hold across diverse samples and align with social presence theory, which suggests that cues signaling an interpersonal agent foster positive communication outcomes like enjoyment and interaction . For educational blogs where reader retention is a primary goal, this boost in affective and behavioral engagement represents a clear practical benefit of humanization.
In contrast, objective learning outcomes are heterogeneous. Numerous studies find no significant difference in recall or transfer between humanized and neutral control texts, suggesting that added social cues are not necessarily detrimental to learning. However, other experiments report small but significant decrements in comprehension, particularly when texts on complex or technical subjects are laden with narrative asides or overt personalization. These findings are well explained by cognitive load theory, which posits that extraneous social information can impose processing demands that interfere with schema construction .
This apparent contradiction is clarified by contextual moderators. Learner expertise and content type are critical: novice learners or those engaging with conceptual or motivational material often show comprehension gains or neutral outcomes, as humanizing elements can provide meaningful scaffolding and context . Conversely, expert audiences and dense technical content are more susceptible to the cognitive costs of social cues, which may be perceived as reducing objectivity. The literature thus points toward a trade-off model: humanization boosts engagement but can, under specific conditions, impose a modest penalty on objective comprehension. This necessitates a strategic alignment of textual voice with audience needs and instructional goals.
Methodological Comparison and Best Practices for Undergraduate Projects
Methodological approaches in the reviewed literature vary across disciplines, yet they are often constrained by common limitations that may explain the inconsistent findings on comprehension. Studies typically employ between-subjects experimental designs, drawing participants from student samples or online convenience panels like Mechanical Turk . While strengths include theory-driven manipulations and the use of multimodal outcomes (self-report, behavioral, and performance-based), recurring weaknesses temper the field’s conclusions. These include underpowered samples, inadequate manipulation and attention checks, a scarcity of preregistered studies, and an overreliance on contrived vignettes rather than authentic blog content, which limits ecological validity.
For undergraduate researchers, addressing these limitations is both feasible and critical for producing valuable contributions. Pragmatic best practices involve designing well-controlled experiments with a priori power calculations to ensure adequate sample sizes (e.g., N ≥ 50 per cell). Including manipulation checks and pairing subjective self-report scales with objective measures, such as a brief comprehension quiz or time-on-task, strengthens causal claims. Furthermore, using ecologically valid stimuli (e.g., high-fidelity mockups of blog posts) and adhering to open-science principles like preregistration and data sharing significantly enhances rigor. Following these steps can make undergraduate investigations credible and potentially publishable as replication or pilot studies.
Gaps in the Literature and Feasible Undergraduate Research Directions
Despite convergent findings on short-term trust, the reviewed literature presents several gaps that limit cumulative knowledge: a scarcity of longitudinal research to assess the durability of effects, an overreliance on Western convenience samples, inconsistent operationalizations of “humanization,” and infrequent use of authentic blog environments, which reduces ecological validity. Additionally, interactions between specific humanizing features and learner characteristics like prior knowledge remain underexplored.
These limitations create opportunities for feasible undergraduate projects capable of yielding meaningful contributions . For instance, a small randomized experiment embedded within an active course blog could test a humanized versus a neutral post, measuring effects on a comprehension quiz and a trust scale to address ecological validity and assess student needs (T. Chan, D. Jo, Andrew W. Shih, V. Bhagirath, L. Castellucci, C. Yeh, Brent Thoma, Eric K Tseng, Kerstin de Wit, 2018). Alternatively, a direct replication of a published vignette study could be improved with robust manipulation checks and open-science practices, clarifying the reliability of prior findings using online panels . A third approach is a cross-sectional study that codes naturally occurring humanizing features in course forums and correlates them with engagement metrics. Each of these designs balances methodological rigor with practical scope, advancing understudied questions about the durability, diversity, and real-world applicability of text humanization.
Counterarguments, Ethical Considerations, and Limitations
Beyond the methodological limitations previously identified, a central counterargument posits that humanizing text can sacrifice perceived expertise for warmth, potentially fostering misplaced trust or reducing critical scrutiny . This concern is particularly salient in high‑stakes technical domains and is compounded by cultural variability, where cues meant to build rapport may be perceived as unprofessional. Ethically, the deliberate manipulation of perceived humanity raises questions of informed consent and deceptive persuasive intent. Consequently, addressing these issues demands both methodological rigor and practical restraint. Mitigating the field’s reliance on convenience samples , triangulating subjective reports with objective outcomes, and preregistering designs are crucial safeguards. In practice, this suggests reserving prominent humanization for novice audiences and motivational content, while exercising caution in technical, high‑stakes instruction.
Implications for Practice and Research, and Conclusion
This review concludes that algorithmically humanized text offers clear gains in short-term engagement and perceived trust but presents a context-dependent trade-off with objective comprehension . For practitioners in educational contexts, this finding underscores the need for strategic application. Humanizing features can effectively foster social presence to build initial reader trust , particularly when tailored to learner needs for motivational or introductory content . However, in dense technical passages where cognitive load may impede learning, a more neutral voice is warranted. For researchers, resolving this trade-off is a primary goal. The methodological gaps identified herein—particularly the need for longitudinal studies and ecologically valid stimuli—offer clear directions for future work. Undergraduate projects that pair subjective and objective measures in controlled, preregistered designs are well-positioned to contribute the cumulative evidence needed to navigate this complex landscape.
Reference
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