A classic narrative (storytelling) structure begins at a start point, builds tension, reaches a point of climax, and then achieves resolution. This structure is found in many texts, written and spoken. LIWC-22 (pronounced “luke”) enables a computational analysis of various texts for various indicators of narrative structure, specifically, staging, plot progression, and cognitive (psychological) tensions. Come see how this tool is applied to various texts and how the resulting information may be used for research and analysis.

1. MAPPING NARRATIVE STRUCTURES
WITH COMPUTATIONAL TEXT ANALYSIS
(LIWC-22)
Shalin Hai-Jew
SIDLIT 2022
July 27 – 29, 2022

2. PRESENTATION OVERVIEW
A classic narrative (storytelling) structure begins at a start point, builds tension,
reaches a point of climax, and then achieves resolution. This structure is found in
many texts, written and spoken. LIWC-22 (pronounced “luke”) enables a
computational analysis of various texts for various indicators of narrative structure,
specifically, staging, plot progression, and cognitive (psychological) tensions. Come
see how this tool is applied to various texts and how the resulting information may be
used for research and analysis.
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3. WHAT IS
A BASIC LINEAR NARRATIVE STRUCTURE
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4. 4

5. A SIMPLE LINEAR NARRATIVE STRUCTURE
A story has a beginning, a middle, and an end.
A linear story unfolds over time, in a kind of chronology.
At the start of a story, there are characters and scenes. Over time, there is rising
tension, and there are important things at risk. The tension reaches a climax, and a
resolution follows.
Based on various storytelling traditions, there are limits to what may happen.
Some suggest that there are universals, like 7 basic (recurring) plots, universal
character archetypes, and others.
 In a sense, every new story is an old story retold, with different variations.
 People enjoy the familiar, and they enjoy the new, in some combination.
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6. WHAT NARRATIVE STRUCTURES ARE
As an ancient form of information-sharing, storytelling (narration) is considered
something for which people are natively good at enjoying and remembering.
Many forms of learning are taught through storytelling structures. People engage in
meaning-making through telling stories, such as stories of origins, of heroes, of values
and justice, of how the universe works, and so on.
 Lived human experiences are inherently episodic and story-based.
Storytelling is inherently part of literature, movies, digital gaming, art, and others.
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7. WHAT IS LIWC-22?
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9. WHAT IS LIWC-22?
LIWC (pronounced “luke”) was created in 1993, to assess emotions (positive or
negative) in human natural language (in written and spoken forms).
Over the years, it has evolved to include many analytical features.
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10. THE BASIC ANALYTICAL RUN
The basic analytical run includes the following:
There are universal language scores around four dimensions: analytic (evaluative
and assessing language), clout (influence-based language), authentic (human-to-
human relational warmth), and tone (positive, neutral, or negative sentiment).
There are analyses of linguistic features of the natural language.
There are punctuation pattern extractions.
There are various forms of psychometrics: human drives, cognition, affect, sociality,
culture, lifestyle, physical, perception, time, and conversational language.
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11. NEW FUNCTIONALITIES TO LIWC-22
(VS. LIWC-2015)
Additional Features Summary
Word Frequencies Word counts of the most frequently used words in a document or (curated)
set of documents
Meaning Extraction Theme extraction from the document or (curated) set of documents
Narrative Arc Analyzing how much of a narrative structure a file has based on three
elements: staging, plot progression, and cognitive tension; positive and
negative emotion
Contextualizer Extracting lead-up words and lead-away words from particular target
words-of-interest
Case Studies Applying multiple analytical modules (of LIWC-22) to one case file at a
time (n=1), for deeper qualitative exploration
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12. WORD FREQUENCIES
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13. MEANING EXTRACTION
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14. NARRATIVE ARC
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15. CONTEXTUALIZER
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16. CASE STUDIES
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17. BASIC PROCESSES WITH
COMPUTATIONAL TEXT ANALYSIS
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18. BASIC CAQDAS PROCESSES
1. Research conceptualization
2. Data collection
3. Curation of data
4. Data cleaning
5. Data coding (manual or
computational or both)
6. Computational processing
7. Data visualization
8. Data analytics
9. Refinement
10. Presentation
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19. 19

20. NARRATIVE ARC
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21. THE EXPLORATION OF NARRATIVE ARC
The narrative arc module explores “how each narrative structure ‘unfolds’ throughout
the story, providing corresponding graphs and metrics that reflect the degree to
which each text resembles a normative narrative shape” (Boyd, Ashokkumar, Seraj, &
Pennebaker, 2022, p. 4).
There are three elements of the narrative structures that unfold over time:
1. “staging”
2. “plot progression”
3. “cognitive tension” (Boyd, Blackburn, et al., 2020)
The findings are portrayed visually in Arc of Narrative (AON) graphs. When the
narrative arc analysis is run in a case study mode, there is a text report that
accompanies the graphs.
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22. NORMATIVE LINEAR NARRATION
LIWC-22 is programmed to identify various language-based patterns.
“Staging” is the phase when a work sets the context. Normatively, it should drop off
once the context is set (unless the plot is complex and has multiple sub-narratives
within).
“Plot progression” is about actions and include action words to advance the story.
“Cognitive tension” refers to the winching up of “psychological tension through some
form of conflict” (“Narrative Arc,” 2022). The typical Arc of Narrative (AON) graph
curve here should be an upside-down “U” in that tension rises and then falls.
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23. TYPICAL NARRATIVE STRUCTURES ON
ARC OF NARRATIVE (AON) GRAPHS
Normative narrative shapes of
“staging” which drops off, “plot
progression” which builds, and
“cognitive tension” which rises
and then falls.
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24. ABOUT “ARC OF NARRATIVE” / AON GRAPHS
“AON” (Arc of Narrative) graphs use nodes to indicate various levels of narrative-
based language.
 In the narrative arc case, they represent (1) staging, (2) plot progression, and (3) cognitive tension.
 The nodes are placed on a graph, with x and y axes.
The Arc of Narrative (AON) graphs here [not to be confused with “activity-on-node”
/ AON graphs] are plotted in progression from left to right, and the number of nodes
depends on the number of sections that the document or document set is broken up in.
(The default sectioning is 5.) Remember that the assumption is that the narrations are
linear, with a trajectory that starts at the beginning and ends at the end.
The “AON” stands for “Arc of Narrative.” A node is . Each node represents a
level of empirically observed activity based on the narrative arc.
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25. SOME WALK-THROUGHS
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26. Q&A TRANSCRIPTS
This set contains 12 International Spy Museum Spycast podcast transcripts.
The Q&As were printed out in .pdf format and then transcoded into MS Word for
processing.
Q&As are not necessarily thought of as having narrative structures even though there
are planned trajectories (often created by the interviewer).
Also, Q&As involve give-and-take, so there are often at least two voices interacting
and often more.
That said, structures may exist in ways that are non-obvious.
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27. COMBINED Q&A FILES
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28. SIX-WORD NOVELS
Some 33 short-form “novels” were taken from a Buzzfeed article (Patel, Jan. 27,
2017).
The various “novels” read like simple quippy observations. A few read like plots.
Does sparsity affect how the narrative arc analysis works given that I have broken
out each “novel” into its own file?
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30. SOME LEVEL OF CONTENT
At the far extreme of very brief 6-word novels, LIWC-22 was not able to extract any
narrative structures.
This is to be expected.
I read documentation that each of the works are split into 5 equal-length segments to
assess for staging / plot progression / cognitive tension. The documentation suggests
that a minimum length of a document should be 250 words (for at least 50 words per
section).
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FIVE CHUNKS…OR MORE

32. WIKIPEDIA ARTICLES AROUND SCRIPTWRITING
This small set contains 14 articles, including some lists.
These were printed out as .pdf from MediaWiki and then transcoded into Word files
for processing.
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33. COMBINED WIKIPEDIA ARTICLES AND LISTS
AROUND SCRIPTWRITING
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34. CASE-BASED
NARRATIVITY STUDY AND REPORT
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35. CASE STUDY W/ NARRATIVITY
(VISUAL AND TEXTUAL OUTPUT)
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36. SOME TYPES OF
ASKABLE RESEARCH QUESTIONS USING
THE NARRATIVE ARC FUNCTIONALITY 36

37. SOME ASKABLE RESEARCH QUESTIONS
What are “baselines” for various document sets in terms of narrative structuring?
Various genres?
 What do these narrative arcs say about the respective curated sets?
How are narrative arcs used for strategic messaging (in a particular context)?
Are there effective anti-narrative patterns in terms of staging, plot progression, and
cognitive tensions that may be useful for particular strategic messaging? Tactical
messaging?
How much narrative construction is used in a particular single work?
On social media, how often are narrative constructions used?
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38. SOME ASKABLE RESEARCH QUESTIONS (CONT.)
How can narrative arc analysis provide relevant feedback for those creating
mediated contents? How can creatives improve work based on narrative arc
feedback?
What can narrative arcs (and other textual understructures) say about authorship?
How can narrative arcs be used with other types of computational text analysis?
Human text analysis?
What can the narrative arc analysis show about whether narrative structure enhances
human learning and memory or not?
 And others.
[Note: The Narrative Arc function is very new, and certainly, there are many users of
LIWC who will apply this capability in creative and interesting empirical research.]
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39. WHAT ABOUT THE NARRATIVE
STRUCTURE OF THIS SLIDESHOW?
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40. THIS SLIDESHOW’S NARRATIVE ARC
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41. THIS SLIDESHOW’S NARRATIVE ARC(CONT.)
There seem to be multiple stages in the slideshow…and indeed, there is first an intro
of classic narration structure…and then the software and its definition of three
aspects of narration structure.
The “plot progression” shows initial dropping of activity words and then a spike and
then a drop again. The activities focused on relate to the software.
The cognitive tension is not the classic upside-down “U” but a precipitous downslope in
the Arc of Narrative (AON) graph. This tool does not evoke psychological tensions
and anxieties, probably. Or hopefully not.
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42. REFERENCES
Boyd, R.L., Ashokkumar, A., Seraj, S., & Pennebaker, J.W. (2022).The development
and psychometric properties of LIWC-22. Austin, TX: University of Texas at Austin.
https://www.liwc.app.
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43. CONTACT
Dr. Shalin Hai-Jew
 ITS
 Kansas State University
 shalin@ksu.edu
 785-532-5262
Some Resources:
LIWC-22 Help
Narrative Arc Analysis in LIWC-22
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