1.
Arguing from a Point of View
Adam Wyner1 and Jodi Schneider2
1 - Department of Computer Science, University of Liverpool
2 – Digital Enterprise Research Institute, National University of Ireland
First International Conference on Agreement Technologies
Centre for Advanced Academic Studies, University of Zagreb
Dubrovnik, Croatia
October 16, 2012

2.
Overview
• Hotel reviews are a source of arguments.
• Point of view is needed to evaluate arguments such as
– The hotel is in an excellent location.
• Therefore we relativise evaluative statements based
on point of view.
• The key point: evaluative statements can be justified
using instantiated argumentation schemes relative to
a user and a domain model.
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3.
Hotel use case
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4.
Positive reviews
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5.
Negative reviews
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6.
TMI
• How much 'bad' spoils what amount of 'good'?
• How do the scores relate to the content? How does the
content justify or argue for the score given?
• How do the comments relate to one another? Linear text &
lists of comments aren’t rich enough: Elaborate network of
point and counterpoint.
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7.
It's all about YOU!
People don't just want “information”
They want information that is
• relevant to them
• appeals to them
• sees things from their point of view.
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8.
Goal
• To support relativised argumentation derived from
distributed, inconsistent information.
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9.
Evaluative expressions use case
- client and travel agent -
I'm going to a conference in venue X in Valencia and need a hotel
room.
Bill
Hotel Valencia is in an excellent location.
Travel agent
Why do you say it is an excellent location?
The hotel is a kilometer from the venue X. And the hotel is in the
old part of the city.
OK, please book it.
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10.
Evaluative expressions use case
- client and travel agent -
I'm going to a conference in venue X in Valencia and need a hotel
room.
Jill
Hotel Valencia is in an excellent location.
Why do you say it is an excellent location?
The hotel is a kilometer from the venue X. And the hotel is in the
old part of the city.
But it is a noisy and trashy old part. And it is too far. Please find me
something else.
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11.
Argument evaluation is user-relative
• Bill & Jill receive the same argument from the travel
agent but evaluate it differently.
• Given the premises
– The hotel is a kilometer from the venue X. And the
hotel is in the old part of the city.
• Bill has accepted the claim
– Hotel Valencia is in an excellent location.
• Given the same premises, Jill has not accepted
the claim (and doesn't even agree with all the
premises).
• Different ways to argue for and against the same claim.
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12.
Approach
• Argumentation schemes are key
– Normative patterns of defeasible reasoning.
– Variables can be seen as targets for information
extraction. Could use text analysis to instantiate.
– Evaluate instantiated arguments using
argumentation frameworks.
• Relativise the instantiated arguments to a
user.
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13.
Argumentation Schemes Overview
• Example scheme from the literature “Credible
source”:
– Instantiated
– Abstract
– Questions used to critique the argument
• Two new schemes for our use case
– “Evaluation of location”
– “Evaluation of quality”
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14.
Argumentation scheme example
- instantiated -
• Normative patterns of defeasible reasoning:
– Dr. Rose is an expert about road safety;
– Dr. Rose asserts that having more speed cameras will save
more lives;
– Having more speed cameras will save lives is a statement
concerning road safety;
– Dr. Rose is credible about road safety;
– and Dr. Rose is reliable;
– Therefore, it is presumably true that having more speed
cameras will save more lives.
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15.
Argumentation scheme example
- abstracted -
• Normative patterns of defeasible reasoning:
– X is an expert about Y;
– X asserts Z;
– Z is a statement concerning Y;
– X is credible about Y;
– and X is reliable;
– therefore, it is presumably true that Z.
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16.
Argumentation scheme example
- critique -
• Questions used to critique the argument:
– How credible is X as an expert source?
– Is the claim about Z consistent with what other
experts assert?
– Is X’s assertion based on evidence?
– Others....
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17.
Use case elements
• New argumentation schemes:
– Evaluation of location.
– Evaluation of quality.
• Instantiate schemes relative to a user model.
• Domain and evaluative terminology.
• User model – selection from domain terminology plus
some terminology for parameters, context of
use, constraints....
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18.
User Information
In this paper, we represent user models by terminology and
instantiated schemes.
In other work, we add these components.
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19.
“Evaluation of location” arg. scheme
- abstract -
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20.
“Evaluation of location” arg. scheme
- Instantiating for Bill & Jill -
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21.
“Evaluation of quality” arg. scheme
-abstract-
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22.
“Evaluation of quality” arg. scheme
-Instantiating for Bill-
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23.
Instantiating for Jill
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24.
Use case elements
• Argumentation schemes:
– Evaluation of location.
– Evaluation of quality.
• Instantiate schemes relative to a user model.
• Domain and evaluative terminology.
• User model – selection from terminology and
instantiated schemes.
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25.
Domain and evaluative terminology
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26.
User-associated inference
• If the instantiations of both argumentation schemes
are acceptable to the user, then the user has a
justification to book the hotel.
• For us, the model of the user can be given in terms of
a logical language – the terminology and the
schemes instantiated with that terminology.
• Arguing about the instantiations, e.g. Jill's criticism of
the travel agent's proposition, is a meta-argument
about the contents of the user model.
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27.
Argumentation frameworks & text analysis
• This paper is part of a larger work on the argumentation
pipeline, from textual source to abstract argumentation.
• Introduces new schemes and instantiates them relative
to a user.
• Other parts:
– We have a text analytic tool (GATE) to support the
extraction of relevant information from the source.
– We have a proposal for integrating this with
argumentation frameworks.
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28.
Argumentation pipeline
Source Text
Instantiated Abstract Argumentation
No fresh orange juice at Argumentation Schemes Frameworks
breakfast and besides terrible
filter coffee extra payment for
cappuchino etc... No wifi in the
rooms (says so in
description, but still...). AS1: ....
Relate
Extract text
schemes to
Very impressive hotel with to schemes arguments.
stunning views. Staff were
attentive - especially the bell
boys. 5 min bus journey to the AS2: ....
old town or 15 min walk. The
room was very comfortable.
If u want to stay with comfort I
would never recommend this
hotel on arrival I was waiting AS3: ....
my room from 14.00 till
16.00, but again they gave me a
room with two separate beds
ignoring my comments in the
booking (one king bed and big
bathtube)
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29.
Consumer argumentation scheme
Variables in schemes as targets for extraction.
Premises:
• Camera X has property P.
• Property P promotes value V for agent A.
Conclusion:
• Agent A should Action Camera X.
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30.
Identifying and extracting text
• Annotate text:
– Simple or complex annotations.
– Highlight annotations with
– Search for and extract text by annotation.
• GATE “General Architecture for Text Engineering”.
– Works with large corpora of text.
– Rule-based or machine-learning approaches.
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31.
,
,
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32.
Query for patterns
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33.
An argument for buying the camera
Premises:
The pictures are perfectly exposed.
The pictures are well-focused.
No camera shake.
Good video quality.
Each of these properties promotes image quality.
Conclusion:
(You, the reader,) should buy the CanonSX220.
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34.
An argument for NOT buying the
camera
Premises:
The colour is poor when using the flash.
The images are not crisp when using the flash.
The flash causes a shadow.
Each of these properties demotes image quality.
Conclusion:
(You, the reader,) should not buy the CanonSX220.
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35.
Counterarguments to the premises of
“Don’t buy”
The colour is poor when using the flash.
For good colour, use the colour setting, not the flash.
The images are not crisp when using the flash.
No need to use flash even in low light.
The flash causes a shadow.
There is a corrective video about the flash shadow.
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36.
Argumentation Frameworks
• <Arguments, Relation>, where
arguments are atomic nodes
and the relation is attack.
• Calculate the sets of nodes that
are 'compatible'.
• Articulate nodes with a logical
language of literals and
rules, where attack is
contrariness between
Preferred Extension of the AF.
expressions of the language.
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37.
Future work
• User model formalisation and meta-argumentation.
• Text analysis for this set of data.
• Tool refinement.
• Add ontology modules to the tool.
• Multi-critierial argumentation – properties ascribed
to the argument vs. premises of the argument.
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38.
Related Papers
• Wyner, van Engers, and Hunter (2010). "Working on the Argument
Pipeline: Through Flow Issues between Natural Language
Argument, Instantiated Arguments, and Argumentation
Frameworks", Workshop on Computational Models of Natural
Argument (CMNA).
• Wyner, Schneider, Atkinson, and Bench-Capon (2012). ''Semi-
automated argumentation analysis of online product
reviews'', Conference on Computational Models of Argument
(COMMA).
• Schneider and Wyner (2012). ''Identifying consumers' arguments in
text'', Workshop on Semantic Web and Information Extraction
(SWAIE at EKAW).
• Schneider, Davis, and Wyner (2012). ''Dimensions of argumentation
in social media'', Conference on Knowledge Engineering and
Knowledge Management (EKAW).
October 16, 2012 Wyner and Schneider, AT 2012 37

39.
Acknowledgements
• FP7-ICT-2009-4 Programme, IMPACT Project, Grant
Agreement Number 247228.
• Science Foundation Ireland Grant No. SFI/08/CE/I1380 (Líon-
2). Short-term Scientific Mission grant from COST Action
IC0801 on Agreement Technologies. SFI Short Term Travel
Fellowship.
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40.
Thanks for your attention!
• Questions?
• Contacts:
– Adam Wyner adam@wyner.info
– Jodi Schneider jschneider@pobox.com
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