LogosLink User's Manual
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LogosLink version 2.0.2
C3 Analytics (Corpus)
C3 analytics shows the correlations between centrality, cogency and contentiousness for context elements linked to propositions in the corpus argumentation models.
This is useful to determine whether any two of these three variables are correlated in some way across the corpus.
Parameters
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Agent.
If a reference context exists and you select an agent, only the propositions of speakers linked to this agent will be taken into account when aggregating argumentation results.
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Contentiousness exponent.
This indicates the weight of attacks and supports on a proposition when calculating its contentiousness.
Typical values are between 2 and 5.
Results
Results are given separately for linked themes and positions.
The total number of argumentation models used by the analytics is shown at the top as "Argumentatin model count".
Argumentation models are gathered from the following sources:
- Dependent argumentation models of active documents.
Linked Themes
Results are shown as some overall data and three scatterplot charts.
Overall data
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Centrality/Cogency ρ.
This is the correlation coefficient for centrality and cogency.
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Centrality/Contentiousness ρ.
This is the correlation coefficient for centrality and contentiousness.
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Cogency/Contentiousness ρ.
This is the correlation coefficient for cogency and contentiousness.
Correlation coefficients indicate how strongly values for the two variables in propositions across the corpus linked to each theme are related.
Please see the Details section below for more information about correlation coefficients.
Charts
A scatterplot chart is shown for each pair of variables.
Each point in the chart represents a theme in the reference context.
The theme's value for each variable is calculated as the average of the values of the propositions linked to it across the corpus.
Linked Positions
Results are shown as some overall data and three scatterplot charts.
Overall data
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Centrality/Cogency ρ.
This is the correlation coefficient for centrality and cogency.
-
Centrality/Contentiousness ρ.
This is the correlation coefficient for centrality and contentiousness.
-
Cogency/Contentiousness ρ.
This is the correlation coefficient for cogency and contentiousness.
Correlation coefficients indicate how strongly values for the two variables in propositions across the corpus linked to each position are related.
Please see the Details section below for more information about correlation coefficients.
Charts
A scatterplot chart is shown for each pair of variables.
Each point in the chart represents a position in the reference context.
The position's value for each variable is calculated as the average of the values of the propositions linked to it across the corpus.
Details
Correlation coefficients are calculated as population Pearson correlation coefficients .
Their values are between -1 and 1.
A coefficient close to 0 indicates no correlation exists between the variables.
A coefficient close to 1 indicates perfect positive correlation, meaning that as one variable increases, the other variable also increases.
A coefficient close to -1 indicates perfect negative correlation, meaning that as one variable increases, the other variable decreases.
See Also
Contents distributed under a Creative Commons Attribution 4.0 International License
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last updated on 13/06/2025 12:26