Scatterplots of latent dimensions
Feature weights and contributions
Feature values and group means
Corpus text viewer
SEEFLEX: Scatterplots of latent dimensions
NB: The Shiny applications are based on the work by Stephanie Evert and Stella Neumann (Neumann & Evert, 2021). The code can be accessed
here.
Multivariate analysis
PCA
LDA Genre
LDA Curricular task
x-axis (horizontal)
Dimension 1
Dimension 2
Dimension 3
Dimension 4
y-axis (vertical)
Dimension 1
Dimension 2
Dimension 3
Dimension 4
choose a preset:
Default
show all operators
hide all operators
S1: PCA overview (Dim 1:2)
S2: PCA analyze, describe, point out and summarize (Dim 1:2)
S3: PCA CRE tasks (Dim 1:2)
S4: PCA broadcast texts (Dim 1:2)
S5: PCA describe and informal e-mail (Dim 1:2)
S6: PCA IRC tasks (Dim 1:2)
S7: PCA dialogue and speech (Dim 1:2)
S8: LDAg overview (Dim 1:2)
S9: LDAg argumentative texts (Dim 1:2)
S10: LDAg broadcast-related tests (Dim 1:2)
S11: LDAg CRE, ANA, and IRC (Dim 2:3)
S12: LDAg overview (Dim 3:4)
S13: LDAg personal vs. impersonal (Dim 3:4)
S14: LDAt overview (Dim 1:2)
S15: LDAt selected operators (Dim 1:2)
S16: LDAt genre distribution (Dim 1:2)
S17: LDAt ANA, IRC tasks (Dim 1:2)
S18: LDAt sonnet paraphrase, story (Dim 1:2)
Save Preset
Include all textcat selections
Include current zoom
Filter color variable
Operator 17
Operator 25
Curricular task
Genre
Monochrome
Filter symbol variable
Grade
Curricular task
Genre
Monochrome
Confidence ellipses
Operators granularity
17
25
Operators 17
Analysis
Blog post
Characterization
Comment
Description
Dialogue
Diary entry
Formal letter
Informal e-mail
Interior monologue
Magazine
Point out
Report
Sonnet paraphrase
Speech
Story
Summary
Operators 25
Analysis
Assessment
Blog post
Characterization
Comment
Description
Dialogue
Diary entry
Discussion
Explanation
Formal letter
Informal e-mail
Informal letter
Interior monologue
Magazine
News
Outline
Point out
Presentation
Report
Soliloquy
Sonnet Paraphrase
Speech
Story
Summary
Curricular task
Analysis
Argumentative Writing
Creative Writing
Integrated Reading Comprehension
Mediation
Genre
Describing
Entertaining
Explaining
Inquiring
Persuading
Recounting
Responding
Grade level
Year 10
Year 11
Year 12
point size
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SEEFLEX: Feature weights and contributions
NB: The Shiny applications are based on the work by Stephanie Evert and Stella Neumann (Neumann & Evert, 2021). The code can be accessed
here.
Multivariate analysis
PCA
LDA Genre
LDA Curricular task
Dimension
Dimension 1
Dimension 2
Dimension 3
Dimension 4
What
features
weighted
contribution
Choose a preset:
default settings
include all categories
hide all categories
W1: PCA all pronouns per word across operators (Dim 1)
W2: PCA pronouns in dialogue and speech (Dim 1)
W3: PCA pronouns in describe and informal e-mail (Dim 2)
W4: PCA adjectives and attributive adjectives across operators (Dim 2)
W5: PCA overview blog, report, and comment (Dim 3)
W6: PCA IRC overview (Dim 2)
W7: PCA strong negative weights across operators (Dim 3)
W8: PCA modal verbs across operators (Dim 3)
W9: PCA selected features and operators (Dim 4)
W10: LDAg selected operator density (Dim 2)
W11: LDAg CRE and IRC selected features (Dim 1)
W12: LDAg CRE dialogue vs. narration (Dim 1)
W13: LDAg broadcast-related texts (Dim 1)
W14: LDAg ttop_prep_S across operators (Dim 1)
W15: LDAg salutgreet_S across operators (Dim 2)
W16: LDAg imper_S and ttop_verb_S across operators (Dim 3)
W17: LDAg selected operators and features (Dim 4)
W18: LDAt selected operators and features (Dim 1)
W19: LDAt influential features and selected operators (Dim 2)
Save Preset
include all operator selections
Granularity
17
25
Curricular task
Genre
Operators 17
Analysis
Blog post
Characterization
Comment
Description
Dialogue
Diary entry
Formal letter
Informal e-mail
Interior monologue
Magazine
Point out
Report
Sonnet paraphrase
Speech
Story
Summary
Operators 25
Analysis
Assessment
Blog post
Characterization
Comment
Description
Dialogue
Diary entry
Discussion
Explanation
Formal letter
Informal e-mail
Informal letter
Interior monologue
Magazine
News
Outline
Point out
Presentation
Report
Soliloquy
Sonnet Paraphrase
Speech
Story
Summary
Curricular task
Analysis
Argumentative Writing
Creative Writing
Integrated Reading Comprehension
Mediation
Genre
Describing
Entertaining
Explaining
Inquiring
Persuading
Recounting
Responding
Grade level
Year 10
Year 11
Year 12
Linguistic feature selection
All features
Select features
Select weights limit
Select linguistic features
word_S
lexd
nn_W
np_W
nom_W
neo_W
pall_W
pposs_W
prefx_W
ppers1_P
ppers2_P
ppers3_P
pit_P
adj_W
atadj_W
prep_W
fin_S
past_F
will_F
inf_F
pass_F
modal_V
verb_W
coord_F
subord_F
interr_S
imper_S
title_W
salutgreet_S
adv_place_W
adv_time_W
ttex_conj_S
ttex_disc_S
tint_S
ttop_adv_S
ttop_nom_S
ttop_prep_S
ttop_wh_S
ttop_nonfin_S
ttop_subcl_S
ttop_interr_S
ttop_verb_S
Adjust minimum weight
display size
S
M
L
XL
legend in sidebar
set y-axis limit for boxplots
set y-axis limit for discriminant plots
SEEFLEX: Feature values and group means
NB: This part of the app is based on the Shiny applications originally published in
Neumann & Evert (2021)
but was added and published in
Pauls (2025).
Multivariate analysis
PCA
LDA Genre
LDA Curricular task
Dimension
Dimension 1
Dimension 2
Dimension 3
Dimension 4
What
features
weighted
contribution
Choose a preset:
default settings
include all categories
hide all categories
W1: PCA all pronouns per word across operators (Dim 1)
W2: PCA pronouns in dialogue and speech (Dim 1)
W3: PCA pronouns in describe and informal e-mail (Dim 2)
W4: PCA adjectives and attributive adjectives across operators (Dim 2)
W5: PCA overview blog, report, and comment (Dim 3)
W6: PCA IRC overview (Dim 2)
W7: PCA strong negative weights across operators (Dim 3)
W8: PCA modal verbs across operators (Dim 3)
W9: PCA selected features and operators (Dim 4)
W10: LDAg selected operator density (Dim 2)
W11: LDAg CRE and IRC selected features (Dim 1)
W12: LDAg CRE dialogue vs. narration (Dim 1)
W13: LDAg broadcast-related texts (Dim 1)
W14: LDAg ttop_prep_S across operators (Dim 1)
W15: LDAg salutgreet_S across operators (Dim 2)
W16: LDAg imper_S and ttop_verb_S across operators (Dim 3)
W17: LDAg selected operators and features (Dim 4)
W18: LDAt selected operators and features (Dim 1)
W19: LDAt influential features and selected operators (Dim 2)
Operators granularity
17
25
Operators 17
Analysis
Blog post
Characterization
Comment
Description
Dialogue
Diary entry
Formal letter
Informal e-mail
Interior monologue
Magazine
Point out
Report
Sonnet paraphrase
Speech
Story
Summary
Operators 25
Analysis
Assessment
Blog post
Characterization
Comment
Description
Dialogue
Diary entry
Discussion
Explanation
Formal letter
Informal e-mail
Informal letter
Interior monologue
Magazine
News
Outline
Point out
Presentation
Report
Soliloquy
Sonnet Paraphrase
Speech
Story
Summary
Curricular task
Analysis
Argumentative Writing
Creative Writing
Integrated Reading Comprehension
Mediation
Genre
Describing
Entertaining
Explaining
Inquiring
Persuading
Recounting
Responding
Grade level
Year 10
Year 11
Year 12
Linguistic feature selection
All features
Select features
Select linguistic features
word_S
lexd
nn_W
np_W
nom_W
neo_W
pall_W
pposs_W
prefx_W
ppers1_P
ppers2_P
ppers3_P
pit_P
adj_W
atadj_W
prep_W
fin_S
past_F
will_F
inf_F
pass_F
modal_V
verb_W
coord_F
subord_F
interr_S
imper_S
title_W
salutgreet_S
adv_place_W
adv_time_W
ttex_conj_S
ttex_disc_S
tint_S
ttop_adv_S
ttop_nom_S
ttop_prep_S
ttop_wh_S
ttop_nonfin_S
ttop_subcl_S
ttop_interr_S
ttop_verb_S
Summary statistics per operator
Feature values per text
SEEFLEX: Student corpus texts
NB: This part of the app was published in
Pauls (2025).
Enter student ID:
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