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GuidePublished 16 Aug 20269 min readBy KEVOS Editorialbibliometric analysiscontent analysisresearch trendscoding frame
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KEVOS AIBibliometric Trend Analysis as a Research Method

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Bibliometric Trend Analysis as a Research Method

Coding a whole journal against an external standard to chart a field's research trends — the design, the bias-control logic, and the exact point where the exhibit outruns the evidence.

Reading time9 minutes
LevelAdvanced
Topic streamResearch Exemplars
Source materialResearch Exemplars
Updated2026-08-16

In brief

  • The corpus was every research article in one journal across 35 years — 2,015 articles, a whole population rather than a sample.
  • Articles were coded against the knowledge areas of an international standard, explicitly to stop the researcher's own perspective driving the categories.
  • The design has no statistical analysis, no inter-coder check, and no stated search protocol.
  • Its central table places article counts and world events in the same row, inviting the reader to see a correlation the paper concedes it never quantified.

The design

The examined conference paper calls its method "desktop literature research" followed by a comparative analysis mapping research trends against socioeconomic events. In current terminology this is a keyword-and-abstract-based bibliometric content analysis; the paper does not use that label.

THE DESIGN AS STATED

ElementWhat was done
CorpusAll research articles in one leading journal, 1983–2016 — 2,015 articles, the whole population of that outlet for the window
Unit of analysisThe article
Coding frameThe ten knowledge areas of an international project management standard: integration, scope, time, cost, quality, risk, communication, human resource, procurement, stakeholder
Coding basisKeyword and abstract review against those ten areas
Second data streamSocioeconomic and technological events retrieved from research databases, plus reports from an international body covering 1980–2016, matched to trends by keyword search
Country attributionNationality of the first author only
AnalysisFrequency counts by year and knowledge area; a country-count table; a collaboration matrix; visual juxtaposition of counts against dated events

All counts and dates are that study's own. The ten knowledge areas come from an external published standard, not from the study.

Why one journal, and how it was defended

Restricting a field-wide trend study to a single outlet is the design's most obvious vulnerability, and the paper defends it at unusual length with four separate justifications.

  1. The outlet's standing in the field.
  2. That it is written in English, treated as the de facto standard for the field despite prestigious journals existing in other languages.
  3. That its scope aligns with the study's objective, because prior global-trend reviews have appeared in it.
  4. A cited methodological recommendation that investigating one specific reliable journal secures consistency of research topics and yields more meaningful trends than surveying a wider domain.
Note

The fourth justification is the only one that is methodological

Standing, language and scope are arguments about which single journal to pick. Only the fourth argues that a single journal is the right unit at all — and it is borrowed from a prior methodological recommendation rather than demonstrated here.

When you narrow a corpus, separate those two arguments explicitly. Justifying your choice among candidates is not the same as justifying the narrowing.

The bias-control device worth copying

Practice note

Code against an external standard, not against your own themes

The paper's stated rationale for using a published standard's knowledge areas as its categories is explicitly bias control: without an external frame "there is a possibility that a researcher could interpret the trends based on personal perspective and experience".

This is transferable to any content analysis. Author-generated themes are always vulnerable to the objection that the categories were shaped by what the researcher expected to find. Categories taken from a published standard are not — they existed before the analysis and can be inspected independently.

The cost is that the frame may not fit your material, which is exactly what happened here.

The authors note that one of their ten categories shows no consecutive trend because keyword ambiguity makes it hard to classify — a study may be keyword-tagged to one area while its actual purpose belongs to another. They surface the problem themselves and recommend reading further into the article when ambiguity arises. Admitting that a coding frame under-captures one of its own categories is a candid move and a good model.

What the study reported

2,015articles coded across 35 years
70contributing countries
41%of articles from the three most prolific countries
26 / 146lowest and highest annual output
Source example — illustrative only

Population counts from one journal

Every figure above is a count of one outlet's output over one window, with country attributed to the first author only. They describe that journal, not the field.

The first-author attribution matters more than it looks: a paper with authors from three countries counts once, for one country, which systematically understates collaboration in exactly the analysis the paper builds a collaboration matrix for. The paper does not acknowledge this.

The exhibits, and the one that overreaches

HOW THE ARGUMENT IS CARRIED

ExhibitWhat it doesVerdict
Line chart of annual volumeEstablishes growth over the windowSound
Country table, 70 rowsEstablishes concentrationSound, subject to the first-author caveat
Collaboration matrix with a 'Note' column grouping rows by patternTells the reader how to read the groupingA genuinely well-designed exhibit worth copying
Small multiples — ten bar charts, one per knowledge area, each with its own y-scaleLets the reader compare the shapes of trends rather than their magnitudesExcellent technique; the independent y-scales are the point
Three-page table: rows are years, columns are the ten knowledge areas plus a wide 'Socioeconomic Events' columnPlaces counts and world events in the same rowThis is where the exhibit outruns the evidence

Observations about one paper's exhibits.

Caution

When a table is asked to do the work of a statistical test

The three-page table is designed so that article counts and world events sit on the same row. The reader is invited to see a correlation.

The correlation is then asserted narratively — it "can be considered" that research topics and socioeconomic events have a correlation — while the authors concede in the same paragraph that they did not quantify it, because it was outside the research scope.

Both halves are instructive. The juxtaposition is an effective rhetorical device and the exhibit is well built. But the gap between what the layout implies and what the evidence supports is exactly the inferential over-reach a methods reader should be able to name. A table that puts two series side by side is not a correlation analysis, however persuasive it looks.

The paper also explains rises in a knowledge area by naming a plausible contemporaneous event. Confirming instances are supplied; disconfirming ones are not sought. That asymmetry is worth watching for in any trend argument.

What the design leaves out

Source gap

Missing methodological apparatus

For a study coding over two thousand articles, the paper reports:

— no statistical analysis and no correlation coefficient — no inter-coder reliability check, and no indication that more than one person coded — no stated search string, and no inclusion or exclusion protocol — no named software — roughly nineteen references, strikingly few for the corpus size, and used mainly to justify method choices rather than to build an argument

Only one limitation is stated, embedded in the conclusion rather than given its own section: that the correlation was not quantified. The single-journal decision and the first-author attribution — the two more consequential choices — are never acknowledged.

Practice note

What to add if you run this design

  • State the search string, the date window and the inclusion and exclusion rules, so the corpus is reproducible
  • Have a second coder classify a subset and report the agreement rate
  • Attribute multi-author work to all contributing countries, or state plainly that you did not and why
  • If you claim a correlation, compute one — or state that you are describing co-occurrence, and say so in the conclusion as well as the caveat
  • Acknowledge the corpus boundary as a limitation, not only in the justification

When this design is the right choice

Fit test

IfYou want to characterise what a field has studied over time
ThenThis design does that well, and the small-multiples exhibit is an unusually clear way to show it.
IfYou want to claim that external events drove research attention
ThenYou need a quantified relationship, or you need to frame the claim as co-occurrence. Juxtaposition alone will not carry it.
IfYour categories would be your own invention
ThenLook for a published standard or taxonomy to code against first. The bias-control argument is strong and cheap to adopt.
IfYou cannot access a full corpus
ThenState the boundary as a limitation rather than only as a justification — the examined paper does the reverse, and it is the weakest part of its reporting.

How other examined works handled the same reporting obligations is set out in Stating limitations and contribution.

What to carry forward

  1. Coding against an external published standard is a cheap, strong bias-control device. Adopt it where a suitable frame exists.
  2. Small multiples with independent y-scales let a reader compare trend shapes rather than magnitudes. An excellent exhibit.
  3. A table placing two series in the same row is co-occurrence, not correlation, however convincing the layout.
  4. Report the search string, inclusion rules and an inter-coder check. This design reported none of them.
  5. Acknowledge your corpus boundary as a limitation, not only as a justification for the choice you made.

Frequently asked questions

Is analysing one journal defensible?

The examined paper defends it four ways, but only one of those is a methodological argument for narrowing at all — the other three argue which journal to choose. If you narrow a corpus, make both arguments separately and list the boundary in your limitations.

Why code against an external standard?

Because author-generated categories are always open to the objection that they were shaped by what the researcher expected to find. A published standard's categories existed before the analysis and can be inspected independently.

What is wrong with the events table?

Nothing, as an exhibit. The problem is inferential: placing counts and events on the same row invites the reader to see a correlation, which the paper then asserts while conceding it never quantified one.

What is an inter-coder reliability check?

A second person independently codes a subset of the material and the agreement rate is reported. The examined paper does not report one, which for a single-coder study of over two thousand articles is a substantial omission.

Why attribute a paper to the first author's country only?

It is simpler, and the examined study did it. The cost is that multi-country collaborations count once, which systematically understates the collaboration the paper then analyses. Attribute to all countries, or state the choice as a limitation.

References and source attribution

  1. Five examined research works supplied as exemplars: two doctoral theses (1999, 2016), a doctoral portfolio thesis (2004), a peer-reviewed journal paper (2014) and a conference paper (2017/2018). Structural observations only; chapter bodies were not reproduced.
  2. Supplied teaching source, Weeks 2-4: Introduction to Research Methods, Developing a Research Topic, Reviewing the Literature.
  3. Bryman, A. 2016, Social Research Methods, 5th ed., Oxford University Press, Oxford.
  4. O'Leary, Z. 2017, The Essential Guide to Doing Your Research Project, 3rd ed., Sage Publications, London.

Suggested questions for Ask KEVOS

  • Design a bibliometric study of a field I name.
  • What published standard could I use as a coding frame for my topic?
  • How do I report inter-coder reliability?
  • What is the difference between co-occurrence and correlation in a trend study?
  • Write the inclusion and exclusion criteria for a literature corpus.

Related KEVOS knowledge

Risk Scoring with RFMEA: A Worked Analytical MethodAdvanced · research exemplarsResearch Methodologies: An OverviewCore · research methodologyIdentifying the Gap in the LiteratureAdvanced · literature reviewStating Limitations and ContributionCore · research exemplarsData Collection Methods: Data as EvidenceCore · data collectionHow Real Literature Reviews Are OrganisedAdvanced · research exemplars
KEVOS® · Project Delivery · Research Projects Page KVS-PM-RES-0079 · v1.0.0 · content 2026.08 Last reviewed 2026-08-16

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Risk Scoring with RFMEA: A Worked Analytical MethodGuide · Research ProjectsNEXT LESSON →Declaring a Research Paradigm — Or NotGuide · Research ProjectsInterview Design in Project ResearchGuide · Research ProjectsStating Limitations and ContributionGuide · Research Projects
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