• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
Turning social disputes into knowledge representations DERI reading group 2012-03-28
 

Turning social disputes into knowledge representations DERI reading group 2012-03-28

on

  • 1,863 views

A reading group presentation about Turning social disputes into knowledge representations, based primarily on two papers: ...

A reading group presentation about Turning social disputes into knowledge representations, based primarily on two papers:

Toni and Torroni. Bottom-up Argumentation. In: First International Workshop on the Theory and Applications of Formal Argumentation 2011 (TAFA), 16-22 July, 2011, Barcelona, Spain. http://www.doc.ic.ac.uk/~ft/PAPERS/tafaPT.pdf

Benn, Buckingham Shum, Domingue, and Mancini. Ontological Foundations for Scholarly Debate Mapping Technology. In: 2nd International Conference on Computational Models of Argument (COMMA '08), 28-30 May, 2008, Toulouse, France. http://oro.open.ac.uk/11939/

Statistics

Views

Total Views
1,863
Views on SlideShare
923
Embed Views
940

Actions

Likes
1
Downloads
2
Comments
0

4 Embeds 940

http://jodischneider.com 937
http://ranksit.com 1
http://www.commafeed.com 1
http://translate.googleusercontent.com 1

Accessibility

Categories

Upload Details

Uploaded via as Microsoft PowerPoint

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment
  • From http://www.sendareview.com/The Web is full of opinions & commentary.A lot of it disagrees.How do we learn from other people, when they disagree?
  • ==== based on ====Paper title: Ontological Foundations for Scholarly Debate Mapping TechnologyAuthors: Neil Benn, Simon Buckingham Shum, John Domingue, Clara ManciniPublished at: Computational Models of Argument 2008Abstract: Mapping scholarly debates is an important genre of what can be calledKnowledge Domain Analytics (KDA) technology – i.e. technology whichcombines both quantitative and qualitative methods of analysing specialistknowledge domains. However, current KDA technology research has emergedfrom diverse traditions and thus lacks a common conceptual foundation. Thispaper reports on the design of a KDA ontology that aims to provide thisfoundation. The paper then describes the argumentation extensions to theontology for supporting scholarly debate mapping as a special form of KDA anddemonstrates its expressive capabilities using a case study debate.Link: http://oro.open.ac.uk/11939/ANDPaper title: Bottom-Up ArgumentationAuthors: Francesca Toni and Paolo TorroniPublished at: First International Workshop on the Theory and Applications of Formal Argumentation 2011Abstract: Online social platforms, e-commerce sites and technical forasupport the unfolding of informal exchanges, e.g. debates or discussions,that may be topic-driven or serendipitous. We outline a methodology foranalysing these exchanges in computational argumentation terms, thusallowing a formal assessment of the dialectical validity of the positionsdebated in or emerging from the exchanges. Our methodology allowsusers to be engaged in this formal analysis and the assessment, within adynamic process where comments, opinions, objections, as well as linksconnecting them, can all be contributed by users.Link: http://www.doc.ic.ac.uk/~ft/PAPERS/tafaPT.pdf
  • What are the overall opinions?Is there any “knowledge” or consensus here?How can we analyse the conversation?
  • It has been often said that the Web 2.0 is a place for grassroots. Actually, this is exactly what happens here. New contributions and ideas are produced and shared in an exquisitely serendipitous, bottom-up approach. In general, debates in the social Web start with no clear purpose. If the one who posts the first comment has a purpose in mind, he or she does not usually state it. Different is the case of structured debates, or polls in which the objective is clear, for instance choosing one among three possible dates for a meeting. Here instead we are looking at chains of pseudo-random posts, like we find in Facebook, in Amazon or at the bottom of an online newspaper’s article. Sometimes such chains of posts converge to some topic, then again they may totally diverge and focus on some other topic. They may happen to never find a focus.Despite these features, we can still abstract away and recognize, within these exchanges, arguments. But, unlike arguments in the computational argumenta- tion literature, these arguments are not structured or relevant to any predefined topic, opinion or goal. They emerge, bottom-up, from the grassroots. From these arguments, a few mainstream opinions may emerge as the result of many com- ments, as if in a sort of “natural selection”.
  • These coherence parameters are then used as a grammar for defining relations in the merged KDA ontology, including relations between publications, between persons, and between arguments. The benefit of this approach is that rather than implement a multitude of inference rules for inferring positive association, only a limited set of parameterised inference rules need to be implemented. For example, Figure 2(i), which shows a parameterised rule for inferring a +ADDITIVE connection between some Y and some Z, covers typical positive association inferences such as when two arguments support a common third argument or when two publications cite a common third publication. Figure 2(ii), which also shows a parameterised rule, covers typical positive association inferences such as when two persons author a common publication or when two arguments are expressed by a common publication. Finally, Figure 2(iii) covers a typical ‘undercutting’ pattern in argument analysis which is a variation of the social network analysis adage that “the enemy of my enemy is my friend”.
  • http://jodischneider.com/jodi.html
  • The Viewpoints Web is my framework for…
  • Mixed-initiativeGenerate argument maps from conversations (Arvina, MAgtALO)Populate a knowledge baseMaybe change your views
  • They don’t say how they extracted these – but they say Someone makes statement (1)Someone else gives (4) as a reason/premise for (1)Someone else gives (3) as an additional reason for (1)(2) Is a counterproposal with a range of supporting reasons===Icons:http://findicons.com/icon/27954/girl_5?id=27964#http://findicons.com/icon/27930/boy_8?id=27939#http://findicons.com/icon/27955/girl_4?id=27965#
  • Maximal consistent sets
  • Adding funding/collaborators slide.

Turning social disputes into knowledge representations DERI reading group 2012-03-28 Turning social disputes into knowledge representations DERI reading group 2012-03-28 Presentation Transcript

  • Digital Enterprise Research Institute www.deri.ie Turning social disputes into knowledge representations Jodi Schneider DERI Reading Group, Galway, Ireland Wednesday 28th March 2012 Copyright 2011 Digital Enterprise Research Institute. All rights reserved. Enabling Networked Knowledge
  • What can we learn from opinions and social media discussions?Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Digital Enterprise Research Institute www.deri.ie  Toni and Torroni. Bottom-up Argumentation. In: First International Workshop on the Theory and Applications of Formal Argumentation 2011 (TAFA), 16-22 July, 2011, Barcelona, Spain. http://www.doc.ic.ac.uk/~ft/PAPERS/tafaPT.pdf  Benn, Buckingham Shum, Domingue, and Mancini. Ontological Foundations for Scholarly Debate Mapping Technology. In: 2nd International Conference on Computational Models of Argument (COMMA 08), 28-30 May, 2008, Toulouse, France. http://oro.open.ac.uk/11939/ Enabling Networked Knowledge 3
  • From a Facebook thread to logicDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Typical discussionDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Can we make sense of it?Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Discussion featuresDigital Enterprise Research Institute www.deri.ie  Purpose and specific focus are not clear.  Can extract and recognize arguments.  Arguments emerge, bottom-up. Enabling Networked Knowledge
  • Parts of the discussionDigital Enterprise Research Institute www.deri.ie  Comment  Opinion  Links relationships between Comments & Opinions Enabling Networked Knowledge
  •  Comment  “This is what my kitchen tap used to look like…” Opinion  “Separate taps are common in GB” Links  “This is what my kitchen tap used to look like…” supports “Separate taps are common in GB”
  •  Comment  “This is what my kitchen tap used to look like…” Opinion  “Separate taps are common in GB” Links  “This is what my kitchen tap used to look like…” supports “Separate taps are common in GB”
  •  Comment  “This is what my kitchen tap used to look like…” Opinion  “Separate taps are common in GB” Links  “This is what my kitchen tap used to look like…” supports “Separate taps are common in GB”
  •  Comment  “This is what my kitchen tap used to look like…” Opinion  “Separate taps are common in GB” Links  “This is what my kitchen tap used to look like…” supports “Separate taps are common in GB”
  • Mapping the conversationDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • objectsTo linkDigital Enterprise Research Institute www.deri.ie Links  “Separate taps are inconvenient because they freeze/ burn hands” objectsTo “Separate taps are not inconvenient as basin solves temperature problem” Enabling Networked Knowledge
  • Logical frameworkDigital Enterprise Research Institute www.deri.ie  Assumption-Based Argumentation  basedOn(o3) ← c2, l_3_2 Enabling Networked Knowledge 15
  • Logical frameworkDigital Enterprise Research Institute www.deri.ie  Assumption-Based Argumentation  alink(l_4_17,o4,o17) Enabling Networked Knowledge 16
  • Mapping a debate based on its Wikipedia articleDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Extracting scholars’ opinions from WikipediaDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Reference OntologyDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Aligning/SpecialisingDigital Enterprise Research Institute www.deri.ie  Agent  Person  Organisation  Information Object  Publication  Description  PropositionalContent  NonPropositionalContent Enabling Networked Knowledge
  • Debate representationDigital Enterprise Research Institute www.deri.ie  Issues  Propositions  Arguments Enabling Networked Knowledge
  • Debate elementsDigital Enterprise Research Institute www.deri.ie  Issue  Is aborting a zygote, embryo, or fetus a violation of human rights?  Proposition  The existence and moral right to life of human organisms begins at or near conception  Argument  All or almost all abortion should be illegal Enabling Networked Knowledge
  • IssueDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Proposition & ArgumentDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • Cognitive Coherence RelationsDigital Enterprise Research Institute www.deri.ie Additive/Causal Positive/Negative Semantic/Pragmatic Basic/Non-Basic Enabling Networked Knowledge
  • Cognitive Coherence RelationsDigital Enterprise Research Institute www.deri.ie Additive/Causal  Weak correlation  Strong correlation Positive/Negative  Pos: “Because he had political experience, he was elected president”  Neg: “He did not have any political experience, yet he was elected” Semantic/Pragmatic  Factual content  Speech Act – (“Are you warm?” implies “Can I open the window?”) Basic/Non-Basic  Presentation order Enabling Networked Knowledge
  • Cognitive Coherence RelationsDigital Enterprise Research Institute www.deri.ie “Because he had political experience, he was elected president.”  Causal  Positive  Semantic  Basic order “He did not have any political experience, yet he was elected president”  Additive  Negative  Non-basic order Enabling Networked Knowledge
  • Inference RulesDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge 28
  • Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge 29
  • Relationship to my workDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
  • What can we do with it?Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge 31
  • “ELIZA for arguments”Digital Enterprise Research Institute www.deri.ie Snaith, Lawrence, & Reed, “Mixed initiative argument in public deliberation,” ODET 2010 Enabling Networked Knowledge 32
  • Highlight ControversiesDigital Enterprise Research Institute www.deri.ie Ennals, R., Trushkowsky, B., & Agosta, J. M. (2010). Highlighting Disputed Claims on the Web. In WICOW at WWW 2010. Enabling Networked Knowledge
  • Transform Debates into Argument FrameworksDigital Enterprise Research Institute www.deri.ie (1) Households should pay tax for their garbage. (4) (1) Paying tax for garbage increases recycling, so households should pay. Arrow: premise (3) (1) Recycling more is good, so people should van Engers, & Bahreini. Wyner, pay tax for their garbage. From Policy-making Statements to First-order Logic. EGOV 2010 34 Enabling Networked Knowledge
  • Calculate best options (non-contradictory opinions)Digital Enterprise Research Institute www.deri.ie Wyner, van Engers, & Bahreini. From Policy-making Statements to First-order Logic. EGOV 2010 Enabling Networked Knowledge 35
  • How do we make one?Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge 36
  • Frozen Planet EpisodeDigital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge 37
  • AcknowledgmentsDigital Enterprise Research Institute www.deri.ie  Thanks to our collaborators!  Katie Atkinson, Trevor Bench-Capon, Adam Wyner (Liverpool)  DERI Social Software Unit  Rhetorical Structure Taskforce, W3C Health Care/Life Sciences  Funding  Science Foundation Ireland Grant No. SFI/08/CE/I1380 (Líon-2)  Short-term scientific mission (STSM 1868) from the COST Action ICO801 on Agreement Technologies  Upcoming: SFI Travel Supplement Enabling Networked Knowledge 38
  • Thanks!Digital Enterprise Research Institute www.deri.ie jodi.schneider@deri.org http://jodischneider.com/jodi.html @jschneider Enabling Networked Knowledge