What is Forensic Linguistics and 3 Important Cases Where It Was Used

Introduction

Imagine if Sherlock Holmes traded his magnifying glass for a grammar book. That, in essence, is the life of a forensic linguist: someone who solves crimes not through fingerprints or DNA, but through the quirks of language itself. Forensic linguistics is the applied science of analyzing written or spoken language in legal and criminal contexts. The premise is deceptively simple: the way we speak and write leaves behind a unique signature. From ransom notes to online chat logs, our linguistic fingerprints may betray us, even when we try to hide.

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What Is Forensic Linguistics?

Forensic linguistics emerged formally in the 1960s, when British linguist Jan Svartvik analyzed police statements in a murder case and revealed that the supposed confessions contained language inconsistent with the accused’s speech (Coulthard, 2004). Since then, it has grown into an interdisciplinary field drawing on psycholinguistics, sociolinguistics, and criminology.

At its core, forensic linguistics assumes that each person has an idiolect—an individual and relatively stable linguistic style, influenced by cognitive habits, social background, and education. Just as fingerprints identify individuals, so do peculiarities in syntax, vocabulary, and punctuation (Grant, 2010).

Applications of forensic linguistics include:

• Authorship attribution: determining who likely wrote a document.

• Discourse analysis: examining how police interrogations or witness statements may be shaped by leading language.

• Threat assessment: analyzing anonymous threats, ransom notes, or online messages.

• Trademark and contract disputes: clarifying ambiguous legal language.

Forensic linguistics straddles both the hard sciences (through quantitative methods and statistics) and the social sciences (through interpretation and psychology).

Famous Cases

The popular imagination often credits DNA with cracking impossible cases, but language has played just as powerful a role.

The Unabomber
Perhaps the most famous case in forensic linguistics is that of Ted Kaczynski, the “Unabomber.” For nearly two decades, Kaczynski terrorized the United States with letter bombs. When his manifesto, Industrial Society and Its Future, was published in 1995, FBI linguist James R. Fitzgerald recognized unusual phrasings such as the proverb “You can’t eat your cake and have it too” in reverse order (“You can’t have your cake and eat it too”). This odd linguistic habit matched earlier letters written by Kaczynski, helping to confirm his authorship (Olsson, 2004).

Derek Bentley Case
In the 1950s, Derek Bentley was convicted of murder based in part on police statements attributed to him. Decades later, forensic linguist Malcolm Coulthard demonstrated that the written confession contained phrases Bentley was unlikely to use, pointing instead to police authorship. This contributed to Bentley’s posthumous pardon (Coulthard, 1994).

Ransom Notes and Threats
In the JonBenét Ramsey case, forensic linguists examined a suspicious ransom note. Its length, phrasing, and rhetorical flourishes were highly unusual for genuine ransom demands, suggesting it may have been staged (McMenamin, 2002). In other investigations, unique regionalisms have been revealing—for example, the term devil strip (for the grassy patch between sidewalk and street) identified a suspect from Ohio (Shuy, 2006).

These examples show how criminals often leave unintentional linguistic clues, exposing thought patterns, background, and even psychological state.

The Psychology of Linguistic Fingerprints

Why do these quirks emerge? From a psychological perspective, language production is a semi-automatic process. While we can consciously choose words to disguise our identity, we rarely control every stylistic habit—such as punctuation, spelling variants, or the order of idioms. These unconscious features stem from deeply ingrained memory patterns, cognitive biases, and learned routines (Tiersma & Solan, 2012).

Moreover, emotions influence language in predictable ways. Research on threatening communications shows that heightened arousal (such as anger or fear) often leads to shorter sentences, increased repetition, and certain grammatical constructions (Gales, 2010). An analyst can therefore detect not only authorship, but also the psychological state of the writer.

This intersection with psychology makes forensic linguistics powerful: it reveals both who is likely speaking and why they speak the way they do.

Methods of Analysis

Forensic linguists use a blend of qualitative and quantitative methods:

1. Comparative stylistics: Comparing disputed texts with known writing samples for consistency in spelling, syntax, or vocabulary.

2. Corpus linguistics: Using databases of language to test whether certain phrases are common or rare.

3. Statistical models: Employing machine learning to measure word frequency, collocations, or stylistic markers (Chaski, 2001).

4. Pragmatic analysis: Studying how meaning is conveyed through tone, politeness strategies, or indirect speech.

For example, two suspects might both spell because as becuz, but only one consistently uses double exclamation marks (!!) in casual writing. These small signals build a linguistic profile.

Limitations and Critiques

Despite its successes, forensic linguistics faces criticism. Courts require high standards for scientific evidence, and some argue that linguistic analysis is too interpretive. Butters (2010) notes that comparing short texts, like ransom notes, can lead to over-interpretation because of limited data. Others stress that differences in genre (e.g., emails vs. graffiti) complicate comparisons.

To address these issues, computational approaches are becoming more important. Algorithms can analyze thousands of features simultaneously, offering more objective assessments of authorship (Grant, 2013). Still, most experts argue that linguistic evidence should supplement, not replace, other forms of forensic proof.

Fun Modern Twists

The digital age has introduced new forms of linguistic evidence. Emojis, for example, can serve as personal signatures—some people consistently use 🌸 instead of 🌹, or prefer 😂 over 😅. Similarly, texting habits (such as spacing after punctuation or use of lowercase “i”) can distinguish individuals.

A growing frontier is distinguishing human writing from AI-generated text. Forensic linguists are beginning to ask whether machine-written messages show detectable patterns that differ from human cognitive quirks (Hernandez & Gupta, 2023). In an ironic twist, as criminals turn to AI to generate anonymous threats, linguists may end up analyzing not only human psychology, but artificial “idiolects.”

Conclusion

Forensic linguistics demonstrates that words are never neutral. Every sentence we write is shaped by psychological processes, cultural influences, and individual quirks. Criminals may change disguises, burn fingerprints, or wipe DNA, but they often cannot suppress the unconscious traces embedded in language.

As cases from the Unabomber to JonBenét Ramsey show, words can betray the writer’s mind as effectively as any fingerprint. While challenges remain in ensuring scientific rigor, forensic linguistics is fast becoming a respected tool in the criminal justice system. And beyond the courtroom, it reminds us of a profound truth: every utterance we make is a tiny map of who we are.

References

Butters, R. R. (2010). Forensic linguistics and author identification. Language and Linguistics Compass, 4(9), 704–715. https://doi.org/10.1111/j.1749-818X.2010.00222.x

Chaski, C. E. (2001). Empirical evaluations of language-based author identification techniques. Forensic Linguistics, 8(1), 1–65.

Coulthard, M. (1994). On the use of corpora in the analysis of forensic texts. Forensic Linguistics, 1(1), 27–43.

Coulthard, M. (2004). Author identification, idiolect, and linguistic uniqueness. Applied Linguistics, 25(4), 431–447. https://doi.org/10.1093/applin/25.4.431

Gales, T. (2010). Ideologies of violence: A corpus-assisted discourse analysis of violent threat letters and hate mail. Discourse & Society, 21(3), 308–340. https://doi.org/10.1177/0957926509360658

Grant, T. (2010). Text messaging forensics: TXT 4N6: Idiolect free authorship analysis? International Journal of Speech, Language and the Law, 17(1), 1–20. https://doi.org/10.1558/ijsll.v17i1.1

Grant, T. (2013). TXT 4N6: Method, consistency, and distinctiveness in SMS text messages. In C. Heffer, F. Rock, & J. Conley (Eds.), Legal-Lay Communication: Textual Travels in the Law (pp. 67–87). Oxford University Press.

Hernandez, J., & Gupta, S. (2023). Detecting machine-generated text in forensic contexts: Challenges and opportunities. Forensic Science International: Digital Investigation, 45, 301514. https://doi.org/10.1016/j.fsidi.2023.301514

McMenamin, G. R. (2002). Forensic linguistics: Advances in forensic stylistics. CRC Press.

Olsson, J. (2004). Forensic linguistics: An introduction to language, crime, and the law. Continuum.

Shuy, R. W. (2006). Linguistics in the courtroom: A practical guide. Oxford University Press.

Tiersma, P. M., & Solan, L. M. (2012). The linguist on the witness stand: Forensic linguistics in American courts. Language, 78(2), 221–239. https://doi.org/10.1353/lan.2002.0070