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Argumentative discussions on the web IFIP 2012-10-13
- 1. Digital Enterprise Research Institute www.deri.ie Argumentative Discussions on the Web Jodi Schneider Digital Enterprise Research Institute, NUI Galway Social Networking Semantics and Collective Intelligence working group, International Federation for Information Processing. Galway, Ireland Saturday 13th October 2012 Copyright 2011 Digital Enterprise Research Institute. All rights reserved. Enabling Networked Knowledge 1
- 2. Argumentation is everywhere! Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
- 3. Argumentation is everywhere! Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
- 4. Argumentation is everywhere! Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
- 5. Argumentation is everywhere! Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
- 6. Argumentation is everywhere! Digital Enterprise Research Institute www.deri.ie London Argumentation ForumEnabling April 20, Networked Knowledge 2012
- 7. Identifying arguments is hard. Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
- 9. Approaches Digital Enterprise Research Institute www.deri.ie User support Logical formalisms Theoretical approaches Enabling Networked Knowledge 9
- 10. User Support Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
- 11. Example problems Digital Enterprise Research Institute www.deri.ie Issue a press release responding to Tweet complaints Decide whether to delete a Wikipedia article Based on reviews, determine controversial product features that customers both like & dislike. Enabling Networked Knowledge 11
- 12. Represent Twitter complaints. Digital Enterprise Research Institute www.deri.ie Jodi Schneider Enabling Networked Knowledge 12
- 13. Make sense of deletion discussions Deletion Discussions in Wikipedia: Decision Factors and Outcomes Jodi Schneider, Alexandre Passant & Stefan Decker WikiSym 2012
- 14. Decision Factors for Deleting Articles in Wikipedia Factor Example (used to justify `keep') Notability Anyone covered by another encyclopedic reference is considered notable enough for inclusion in Wikipedia. Sources Basic information about this album at a minimum is certainly verifiable, it's a major label release, and a highly notable band. Maintenance …this article is savable but at its current state, needs a lot of improvement. Bias It is by no means spam (it does not promote the products). Other I'm advocating a blanket "hangon" for all articles on newly- drafted players Deletion Discussions in Wikipedia: Decision Factors and Outcomes Jodi Schneider, Alexandre Passant & Stefan Decker WikiSym 2012
- 15. Alternative Interfaces for Deletion Discussions in Wikipedia: Some Proposals Using Decision Factors. [Demo]” Jodi Schneider and Krystian Samp WikiSym2012
- 16. Find argumentation in reviews Digital Enterprise Research Institute www.deri.ie Enabling Networked Knowledge
- 17. Annotate possible arguments Highlight terms: , Semi-Automated Argumentative Analysis of Online Product Reviews Adam Wyner, Jodi Schneider, Katie Atkinson and Trevor Bench-Capon COMMA 2012
- 18. Find arguments by searching annotations Identifying Consumers' Arguments in Text Jodi Schneider & Adam Wyner, SWAIE at EKAW 2012
- 19. Don’t need flash Identifying Consumers' Arguments in Text Jodi Schneider & Adam Wyner, 19 SWAIE at EKAW 2012
- 20. Flash badly placed Identifying Consumers' Arguments in Text Jodi Schneider & Adam Wyner 20 SWAIE at EKAW 2012
- 21. Simple Reasoning Pattern Digital Enterprise Research Institute www.deri.ie Premises: The Canon SX220 has good video quality. Good video quality promotes image quality for casual photographers. Conclusion: Casual photographers should buy the Canon SX220. Identifying Consumers' Arguments in Text Jodi Schneider & Adam Wyner, SWAIE at EKAW 2012 Enabling Networked Knowledge 21
- 22. Argumentation Scheme Digital Enterprise Research Institute www.deri.ie Premises: The <camera> has <feature>. <feature> promotes <user value> for <user class>. Conclusion: <user class> should <e-commerce action> the <camera>. <e-commerce action>: buy, not buy, sell, return, … Identifying Consumers' Arguments in Text Jodi Schneider & Adam Wyner, SWAIE at EKAW 2012 Enabling Networked Knowledge 22
- 23. Variables as Targets for Digital Enterprise Research Institute Information Extraction www.deri.ie <camera> <property> <user value> <user type> <e-commerce action> Identifying Consumers' Arguments in Text Jodi Schneider & Adam Wyner, SWAIE at EKAW 2012 Enabling Networked Knowledge 23
- 24. Logical formalisms Digital Enterprise Research Institute www.deri.ie Argumentation Schemes Argument Frameworks Assumption-based, Admissible Argumentation (ABBA) Enabling Networked Knowledge
- 25. Formal Representations Digital Enterprise Research Institute www.deri.ie Argumentation Schemes Appeal to Expert Opinion Appeal to Popular Opinion From Analogy Slippery Slope .... Indicate Relevant “Critical Questions” for a discussion Patterns for Information Extraction (Amazon examples - SWAIE 2012) Enabling Networked Knowledge
- 27. Search annotations to fill slots in argumentation scheme Identifying Consumers' Arguments in Text Jodi Schneider & Adam Wyner, SWAIE at EKAW 2012
- 28. Argumentation Frameworks Digital Enterprise Research Institute www.deri.ie Example Variety of Semantics – can be used to choose best options Dung 1995 Enabling Networked Knowledge
- 29. Transform Debates into Digital Enterprise Research Institute Argument Frameworks 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 Wyner, van Engers, & Bahreini pay tax for their garbage. From Policy-making Statements to First-order Logic. EGOV 2010 29 Enabling Networked Knowledge
- 30. Calculate best options Digital Enterprise Research Institute (non-contradictory opinions) www.deri.ie Wyner, van Engers, & Bahreini. From Policy-making Statements to First-order Logic. EGOV 2010 Enabling Networked Knowledge 30
- 31. Assumption-based, Digital Enterprise Research Institute Admissible Argumentation www.deri.ie Deductive system with inference rules Assumptions “Backward argument” – Argument Tree Reasoning on the Web with Assumption-Based Argumentation Francesca Toni Reasoning Web Summer School Enabling Networked Knowledge
- 32. From a Facebook thread to logic Digital Enterprise Research Institute www.deri.ie Toni & Torroni Bottom-Up Argumentation TAFFA 2011 Enabling Networked Knowledge
- 33. 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” Toni & Torroni Bottom-Up Argumentation TAFFA 2011
- 34. Map the conversation Digital Enterprise Research Institute www.deri.ie Toni & Torroni Bottom-Up Argumentation TAFFA 2011 Enabling Networked Knowledge
- 35. objectsTo link Digital 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” Toni & Torroni Bottom-Up Argumentation TAFFA 2011 Enabling Networked Knowledge
- 36. Logical framework Digital Enterprise Research Institute www.deri.ie Assumption-Based Argumentation basedOn(o3) ← c2, l_3_2 Toni & Torroni Bottom-Up Argumentation TAFFA 2011 Enabling Networked Knowledge 36
- 37. Logical framework Digital Enterprise Research Institute www.deri.ie Assumption-Based Argumentation alink(l_4_17,o4,o17) T o n i & T o r Enabling Networked Knowledge r 37 o
- 38. Theories Digital Enterprise Research Institute www.deri.ie Popularity isn’t everything Walton & Krabbe’s Dialogue Types Dimensions of Argumentative Expression Enabling Networked Knowledge
- 39. Numbers aren’t everything Digital Enterprise Research Institute www.deri.ie overwhelming numbers of people may not matter Dimensions of Argumentation in Social Media Jodi Schneider, Brian Davis, and Adam Wyner EKAW 2012 Photograph DAVID GILES/PA NEWS WIRE/AP PHOTO - February 7, 2011 New Yorker via http://www.vincentskeltis.com/blog/2011/2/7/crowd-crush.html Enabling Networked Knowledge
- 40. What’s the Support? Digital Enterprise Research Institute www.deri.ie The overall popularity of an opinion is not as important as the reasons supporting it Dimensions of Argumentation in Social Media Jodi Schneider, Brian Davis, and Adam Wyner EKAW 2012 Image: http://www.nickmilton.com/2012/03/when-people-trust-crowds.html Enabling Networked Knowledge
- 41. Discussion purpose: Digital Enterprise Research Institute Walton & Krabbe’s dialogue types www.deri.ie Commitment in Dialogue: Basic Concepts of Interpersonal Reasoning Walton & Krabbe 1995 Enabling Networked Knowledge 41
- 42. Dimensions of (Argumentative) Digital Enterprise Research Institute Expression www.deri.ie Genre Metadata Properties of users Goals of a particular dialogue Context Informal language Implicit info Sentiment techniques Subjectivity and objectivity Dimensions of Argumentation in Social Media Jodi Schneider, Brian Davis, and Adam Wyner EKAW 2012 Enabling Networked Knowledge
- 43. Acknowledgments Digital Enterprise Research Institute www.deri.ie Thanks to our collaborators! Katie Atkinson, Trevor Bench-Capon, Adam Wyner (Liverpool) DERI Social Software Unit & others Rhetorical Structure Taskforce, W3C Health Care/Life Sciences My 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 SFI Short Term Travel Fellowship Enabling Networked Knowledge 43
- 44. Thanks! Digital Enterprise Research Institute www.deri.ie Questions? Jodi Schneider jodi.schneider@deri.org @jschneider Enabling Networked Knowledge
- 45. 45 http://en.wikipedia.org/wiki/Wikipedia:Articles_for_deletion/Heath_Totten
- 46. Arguments Digital Enterprise Research Institute www.deri.ie Claim: does not merit an article Justification: hasn’t played since 2008, mediocre record Enabling Networked Knowledge 46
Editor's Notes
- http://www.sciencemag.org/content/336/6078/245.full.pdf
- http://news.bbc.co.uk/2/shared/bsp/hi/pdfs/04_04_12_ukconsultation.pdf
- argument map describing the debate on whether computers think took 7,000 hours to complete" (Metzinger, 1999).Metzinger, T. (1999). Teaching philosophy with argumentation maps review of can computers think? the debate by Robert E. Horn. PSYCHE, 5.(as quoted by Clare Llewellyn’s thesis proposal)Map source:http://www.macrovu.com/CCTWeb/CCT1/CCTMap1Emotions.html====Other Examples:FlorisBex, 3 weeks to construct argument map from 1 hour conversationChris Reed’s group, Argument mapping, 8 people for real-time mapping of 45 minute radio broadcastOverview: http://www.arg.dundee.ac.uk/?page_id=645Argument map: http://www.arg.dundee.ac.uk/AIFdb/argview/789BBC Radio 4 Moral Maze 2012-07-18 http://www.bbc.co.uk/programmes/b01ks9zlAnalysis Wall,YouTube video: http://www.youtube.com/watch?v=KVDgH-g8_gU
- 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?
- Collaborative, distributed decision-makingIndividual sense-making informed by many opinionsIndividual decision-making informed by many opinions
- Mainly bright colours in good daylight; flash badly placed
- Isn’t it funny that people tweet about this
- For context, see my longer slidedeck from a reading group presentation about their paper:http://www.slideshare.net/jodischneider/using-controlled-natural-language-and-first-order-logic-to-improve-e-consultation-discussion-forumsreadinggrouptalkThey 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#
- For context, see my longer slidedeck from a reading group presentation about their paper:http://www.slideshare.net/jodischneider/using-controlled-natural-language-and-first-order-logic-to-improve-e-consultation-discussion-forumsreadinggrouptalkMaximal consistent sets
- Via http://www.springerlink.com/content/v7030p6l23l12xl4/fulltext.pdfSeeBondarenko, A., Toni, F., Kowalski, R.A.: An assumption-based framework fornon-monotonic reasoning. In: Pereira, L.M., Nerode, A. (eds.) Proceedings of the2nd International Workshop on Logic Programming and Non-monotonic Reasoning(LPNMR 1993), pp. 171–189. MIT Press, Lisbon (1993)
- For more context, see their paper or my reading group slideshttp://www.slideshare.net/jodischneider/turning-social-disputes-into-knowledge-representations-deri-reading-group-2012-0328
- For more context, see their paper or my reading group slideshttp://www.slideshare.net/jodischneider/turning-social-disputes-into-knowledge-representations-deri-reading-group-2012-0328
- For more context, see their paper or my reading group slideshttp://www.slideshare.net/jodischneider/turning-social-disputes-into-knowledge-representations-deri-reading-group-2012-0328
- For more context, see their paper or my reading group slideshttp://www.slideshare.net/jodischneider/turning-social-disputes-into-knowledge-representations-deri-reading-group-2012-0328
- For more context, see their paper or my reading group slideshttp://www.slideshare.net/jodischneider/turning-social-disputes-into-knowledge-representations-deri-reading-group-2012-0328
- For more context, see their paper or my reading group slideshttp://www.slideshare.net/jodischneider/turning-social-disputes-into-knowledge-representations-deri-reading-group-2012-0328
- . The issue is whether it is the right product for the buyer, which is a matter not only of the pros and cons, but also of the explanations and counterarguments given. In our view, current approaches detect problems, but obscure the chains of reasoning about them.
- . The issue is whether it is the right product for the buyer, which is a matter not only of the pros and cons, but also of the explanations and counterarguments given. In our view, current approaches detect problems, but obscure the chains of reasoning about them.
- 4 Dimensions of ExpressionTo extract well-formed knowledge bases of argument, we must first chart out the various dimensions of social media, to point the way towards the aspects that argumentation reconstruction will need to consider, so that we later can isolate these aspects.Social media encompasses numerous genres, each with their own conversational styles, which affect what sort of rhetoric and arguments may be made. One key feature is the extent to which a medium is used for broadcasts (e.g. monologues) versus conversations (e.g. dialogues), and in each genre, a prototypical message or messages could be described, but these vary across genres due to social conventions and technical constraints. De Moor and Efimova compared rhetorical and argumentative aspects[4] of listservs and blogs, identifying features such as the likelihood that messages receive responses, and whether spaces are owned communities or by a single individual, and the timeline for replies [5]. Important message characteristics include the typical and allowable message length (e.g. space limitations on microblogs) and whether messages may be continually refined by a group (such as in StackOverflow).Metadata associated with a post (such as poster, timestamp, and subject line for listservs) and additional structure (such as pingbacks and links for blogs) can also be used for argumentation. For example, a user’s most recent post is generally taken to identify their current view, while relationships between messages can indicate a shared topic, and may be associated with agreement or disagreement.Users are different, and properties of users are factors that contribute not only to substance of the user’s comment, but as well to how they react to the comments of others. These include demographic information such as the user’s age, gender, location, education, and so on. In a specific domain, additional user expectations or constraints could also be added. Different users are persuaded by different kinds of information. Therefore, to solve peoples’ problems, based on knowledge bases, when dealing with inconsistency, understanding the purposes and goals that people have would be useful.Therefore, the goals of a particular dialogue also matter. These have been considered in argumentation theory: Walton & Krabbe have categorized dialogue types based on the initial situation, participant’s goal, and the goal of the dialogue [11]. The types they distinguish are inquiry, discovery, information seeking, deliberation, persuasion, negotiation and eristic. These are abstractions–any single conversation moves through various dialogue types. For example, a deliberation may be paused in order to delve into information seeking, then resumed once the needed information has been obtained.Higher level context would also be useful: different amounts of certainty are needed for different purposes. Some of that is inherent in a task: Reasoning about what kind of medical treatment to seek for a long-term illness, based on PatientsLikeMe, requires more certainty than deciding what to buy based on product reviews.Informal language is very typically found in social media. Generic language processing issues, with misspellings and abbreviations, slang, language mixing emoticons, and unusual use of punctuation, must be resolved in order to enable text mining (and subsequently argumentation mining) on informal language. Indirect forms of speech, such as sarcasm, irony, and innuendo, are also common. A step-by-step approach, focusing first on what can be handled, is necessary.Another aspect of the informality is that much information is left implicit. Therefore, inferring from context is essential. Elliptical statements require us to infer common world knowledge, and connecting to existing knowledge bases will be needed.We apply sentiment techniques to provide candidates for argumentation mining and especially to identify textual markers of subjectivity and objectivity. The arguments that are made about or against purported facts have a different form from the arguments that are made about opinions. Arguments about objective statements provide the reasons for believing a purported fact or how certain it is. Subjective arguments might indicate, for instance, which users would benefit from a service or product (those similar to the poster). Another area where subjective arguments may appear is discussions of the trust and credibility about the people making the arguments.
- Adding funding/collaborators slide.
- Delete the article]...hasn't played since 2008. His 66-73 record is far from stellar and, in my opinion, does not merit an article.