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Table 1. Examples of argument schemes (our adaptation from Walton, 2006)
Argument
scheme
Argument Structure
Critical questions
Ground
: E is an
expert in the domain
A is in
Warrant
: trust what
expert says
How credible is E (reliable, free of conflict of interests, authorita-
tive, etc.)?
Is E an expert in the field A is in?
Is E's assertion based on evidence?
Expert opinion
G
: A is generally ac-
cepted as true
W
: Believe what is
generally accepted
as true
What evidence (e.g. polls) supports that A is generally accepted?
Even if A is generally accepted, there are any reason for doubting
it is true?
Popular opinion
G
: Case C1 is similar
to case C2, A is true
in C1
W
: repeat things that
have proven to work
well in the past
Are there differences between C1 and C2?
Was A correct (true) in C1?
Is there any other case C3 similar to C1 in which A was not cor-
rect/true?
Analogy
Is the correlation supported by credible evidence?
Is the correlations due to coincidence?
Could there be some factor C causing both A and B?
Are there any other consequences to A that should be taken in the
account?
What evidence support that given A, B will really occur?
What factors can prevent the causal chain to happen and how
much are they probable? What is the weakest link of this chain?
How much is the probability that the chain will actually start?
G:
there is a positive
correlation between A
and B
W
: find out causal
relationships between
things happening
together
Causal (contains
as variant the
argument form
consequences
and the slippery
slope argument)
posed by users and check if critical questions are
adequately answered, and to help authors to check
if their arguments are defendable with respect to
the critical questions and, if not, to revise.
By merging the IBIS, Toulmin and Walton
approaches we represent arguments through
argument nets. We define and argument net as
a directed graph made up of nodes (claims) and
arcs (relationship between claims). A claim can
be the premise or conclusion of an argument and
can be considered to be true to a
certain degree
(e.g. based on the level of consensus assigned
to it by an audience). An arc links two claims,
specifically a premise to a conclusion. It transfers
the degree of truth of the premise to the conclu-
sion. Arcs have a semantics related to the specific
argument scheme through which they transfer the
truth from the premise to the conclusion (e.g. a
“causal” semantic according to which a premise
A causes a conclusion B, as in “wet weather will
make you sick”).
The arc semantics, assigned by users, describes
the way the conclusion is “inferred” from the
premise. Even if argumentative reasoning is not
logical reasoning, one can assume the two are
similar in that they aim to convince viewers about
the truth of a proposition, by “proving” it on the
basis of given premises. An example of argument
net is shown in figure 4.
The proposed representation is aimed at
helping people distinguish between the input
(
grounds
)
of
an argument (i.e. facts, evidence,
shared opinions, values, etc.) and the reasoning
scheme through which an acceptable conclusion
is obtained from the available inputs. This critical
distinction is made for two reasons: i) to encour-
age evidence-based reasoning; and ii) to induce
users to consider the validity of an argument by
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