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1.
voters can endorse the existing arguments
to support the idea;
and Aakhus, 2006; Kirschner et al. 2003; Mancini
and Buckingham Shum, 2006; Rawhan, Zablith
and Reed, 2007). The majority of works in this
area shares a focus on the use of internet related
technologies to implement argumentation frame-
works and environments aimed at improving the
quality of collective debates and decisions and,
more generally, knowledge representation, sharing
and transfer. The idea is to exploit the intrinsic
structure of argumentation:
2.
authors can propose new supporting argu-
ments;
3.
voters can read the attacking arguments and
get convinced that the Hydrogen economy
is not such a good idea, so they can change
their mind and reconsider their support for
the idea.
Argument representation
•
to represent knowledge in a compact and
structured way compared to traditional
textual representation (knowledge sum-
marization),
There is a huge body of research about argument
analysis and structure with implications for map-
ping and representation. We can classify this
research into two major branches:
•
to retrieve knowledge and connections
among pieces of information (creating
knowledge networks),
•
philosophical inquiries
(e.g. the New Rheto-
ric of Perelman, the Informal Logic of Toul-
min, Habermas' Theory of Communicative
Action);
•
artificial intelligence and computer sci-
ence
, starting from the early efforts of the
so called Yale School (Galambos, Abelson
and Black, 1986; Schank, 1986) on case
based reasoning to more recent works on
argumentative agents and the use of argu-
ments in hypertext, knowledge management
and the semantic web (see the recent special
issue on Argumentation published by the
journal Artificial Intelligence in 2007).
•
to foster debate through argumentative
dialogues on the net between users in which
ongoing “mass conversations” made by ar-
guments, endorsements and attacks should
favor the emergence of more plausible,
convincing and shared conclusions about a
given topic (convergence) by allowing at the
same time a certain amount of conflict.
Several attempts have been made to propose
suitable argument representations to achieve these
aims. We can classify these attempts using a con-
tinuum defined by the degree of formalization, and
by the standardization of the proposed argument
format. For instance, Rahwan et al. (2007) pro-
pose a highly structured formalization called the
Argument Interchange Format (AIF), based on a
RDF Schema Semantic Web-based ontology lan-
guage. Such formats have the advantage of being
understood by the machines that are supposed to
process such information, such as argumentative
agents, but are hard for humans to use. In cases
where human involvement is high, we need to
look for less-formal argument representations that
let people easily perform typical argumentative
The applications related to the first area are
mainly in the field of education and legal argu-
mentation, while the second stream has elicited
a remarkable degree of attention in different
areas of artificial intelligence. In the last decade,
considerable effort has been invested by several
researchers in the attempt to find a synthesis of
these two schools of thought, and to consider
several internet related emerging phenomena
as field of application. We can call this attempt
a socio-technical perspective on argumentation
(Carter, 2000; Chesnevar et al., 2006; de Moor
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