Longitudinal Metaphor Analysis — Tracking Conceptual Change Over Time
Longitudinal Metaphor Analysis · Also known as: LMA, diachronic metaphor analysis, longitudinal conceptual metaphor study, repeated-measures metaphor analysis
Longitudinal Metaphor Analysis (LMA) is a qualitative method that tracks how individuals or groups use metaphors across multiple time points to reveal conceptual, attitudinal, or identity shifts. Grounded in conceptual metaphor theory and discourse dynamics, it treats metaphor not as mere rhetorical decoration but as a window into evolving thought, belief, and meaning-making over time.
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When to use it
Use Longitudinal Metaphor Analysis when your research question concerns how understanding, identity, attitudes, or beliefs change over time, and when you have access to the same participants or comparable text sources at multiple time points. It is particularly well-suited to studies of professional identity development, attitude change, educational transformation, policy discourse evolution, or therapeutic change. The method requires rich natural or interview-generated language data at a minimum of two waves; three or more waves allow richer trend analysis. Do NOT use LMA if you have only a single time point (use standard metaphor analysis instead), if your data are purely numerical, or if the aim is frequency-level statistical comparison across large corpora (corpus linguistics tools are more appropriate in that case).
Strengths & limitations
- Reveals conceptual and attitudinal change that retrospective self-report instruments cannot capture accurately.
- Treats language as a direct index of cognition, grounding interpretation in participants' own words rather than researcher-imposed categories.
- Sensitive to both gradual drift and sudden conceptual ruptures in how people frame their experience.
- Compatible with many data types — interviews, diaries, focus groups, written documents — making it flexible across disciplines.
- Can be combined with other qualitative methods (narrative analysis, discourse analysis) for triangulated insight.
- Requires sustained participant access over time; attrition between waves reduces the longitudinal sample and can introduce selection bias.
- Metaphor identification is labour-intensive and requires trained coders; inter-rater reliability must be established and reported.
- Conceptual metaphor mapping involves interpretive judgements that can vary between researchers, requiring explicit reflexivity.
- Cannot establish causal mechanisms — the method documents that conceptual change occurred, not what caused it.
- Small longitudinal samples limit transferability; findings describe a particular group's trajectory rather than general population trends.
Frequently asked
How is Longitudinal Metaphor Analysis different from ordinary metaphor analysis?
Standard metaphor analysis examines metaphor use at a single time point — it describes the conceptual frames present in a text or corpus. Longitudinal Metaphor Analysis adds a temporal dimension: it tracks whether and how those conceptual frames shift across two or more data-collection waves for the same participants or comparable texts. The key contribution is documenting change, stability, or trajectory rather than a static snapshot.
How many time points do I need?
A minimum of two time points is required; otherwise the design is cross-sectional, not longitudinal. Two waves allow a before-after comparison. Three or more waves reveal whether change is gradual and linear, accelerating, or involves reversal. The appropriate number depends on your research question and the expected timescale of the conceptual change you are investigating.
Which metaphor identification protocol should I use?
The MIP (Metaphor Identification Procedure, Pragglejaz Group 2007) and its extended version MIPVU (Steen et al. 2010) are the most widely cited systematic procedures. Both work bottom-up from lexical units in context and require checking whether a word's contextual meaning differs from its most basic meaning in a way that can be understood through comparison. Using an established protocol makes your identification decisions transparent and replicable.
Can I use software for longitudinal metaphor analysis?
Qualitative data management tools such as NVivo or ATLAS.ti can store, organise, and retrieve coded metaphors across waves, and corpus tools can assist with frequency tracking in large datasets. However, the core intellectual work — identifying metaphors, mapping them to conceptual domains, and interpreting cross-wave change — requires human judgement. Software manages the data; the analyst makes the interpretive decisions.
How do I handle participant attrition across waves?
Report attrition transparently: note how many participants provided data at each wave and whether those who dropped out differed systematically from those who remained. Analyse the longitudinal subsample (participants present at all waves) separately from any partial-wave participants. Avoid treating attrition as ignorable, since those who drop out may hold distinctive perspectives whose absence shapes the metaphor landscape you observe.
Sources
- Cameron, L., & Maslen, R. (Eds.). (2010). Metaphor Analysis: Research Practice in Applied Linguistics, Social Sciences and the Humanities. Equinox. ISBN: 978-1845531140
- Cameron, L., Maslen, R., Todd, Z., Maule, J., Stratton, P., & Stanley, N. (2009). The discourse dynamics approach to metaphor and metaphor-led discourse analysis. Metaphor and Symbol, 24(2), 63–89. link ↗
How to cite this page
ScholarGate. (2026, June 3). Longitudinal Metaphor Analysis. ScholarGate. https://scholargate.app/en/qualitative/longitudinal-metaphor-analysis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Content AnalysisQualitative↔ compare
- Discourse AnalysisQualitative Research↔ compare
- Metaphor AnalysisQualitative↔ compare
- Narrative AnalysisQualitative↔ compare
- Thematic AnalysisQualitative Research↔ compare