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Record W2122303692 · doi:10.1109/hicss.2007.238

Genre, Narrative and the "Nigerian Letter" in Electronic Mail

2007· article· en· W2122303692 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsLustNarrativeTone (literature)Internet privacyComputer scienceKey (lock)AdvertisingMythologyWorld Wide WebElectronic mailComputer securityPsychologyBusinessLiteratureArt

Abstract

fetched live from OpenAlex

Spam, or unsolicited email, has become an unavoidable fact of life for anyone with an email account. Spam emails generally reflect genres seen in traditional print format such as advertisements, memos, etc. One particularly interesting form of spam is the "Nigerian letter". Nigerian letters offer "get rich quick" schemes to engage recipients into advance fee fraud activities. This paper provides an empirical analysis of 111 Nigerian letters received by email to explore key elements including the use of form, purpose, and tone. We propose that the use of rich narrative appeals to strong emotions like greed, guilt and lust, and invokes archetypal myths of windfall fortunes in an effort to illicit behaviors which, for the most part, are counter-factual

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score0.110

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.228
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations33
Published2007
Admission routes1
Has abstractyes

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Same topicDigital Communication and LanguageFrench-language works237,207