Flashcards
Argumentation Theory
Flashcards do conjunto (76)
- 1Big dataThe data that is produced faster than we can process it
- 23VsVolume, Velocity, Variety
- 3Big data and industryAmazon, eBay (90PB warehouse), Facebook (50b photos), Google (100b searches per month)
- 4Big data and academiaBritish investment 'Big Data and Energy Efficient Computing, strengthen Europe's position in providing, fast growing
- 5Processing challengesAnalysis, capture, search, share, store, visualisation, management, information privacy
- 6Computational linguisticsStatistical or rule based modelling of natural language
- 7NLPInteractions between computers and human languages
- 8Data miningAutomatic extraction of data, often numerical
- 9Text miningAutomatic extraction of data from natural language texts
- 10Argument Web- Vision for integrated, reusable resources connecting views, opinions, arguments and debates online wherever they may occur
- Aims to create a Web infrastructure that allows for storage and automatic retrieval and analysis of linked argument data
- Web platform combining linked argument data with software tools that make searching the web more intelligent & robust, and make online debate intuitive for its participants, including mediators,
students, academics, broadcasters, and bloggers - 11Theory Neutrality (Reed and Rowe 2005)Sufficient features of Arg common to most theories and concepts to form a common Interlingua
- 12Argument Interchange Format (AIF)Description, standard and series of implementations of a mechanism for exchanging argument resources between tools
- 13Argument analysismanually recognising and diagramming argument data
- 14Argument miningAutomatically recognising and extracting argument data
- 15Argument analyticsAutomatically sense-making of argument and debate
- 16Use of Argument WebArgument analysis, online debating, research tool, evaluation tools (Argugrader), blogging (co-constructed arguments), visualisation
- 17Basic argument structureScheme (Palau & Moens 2009)
Premise, conclusion, argument - 18Swales (1990)Scheme (Teufel et al. 2009)
Aim, textual, own, background, contrast, basis, other - 19Inference Anchoring Theory (Budzynska & Reed 2011)Scheme (Budzynska et al. 2014)
Inference, Conflict, Transition, Illocutionary connections - 20Sentiment analysisMining attitudes towards something
Stock market - 21Opinion miningMining opinions about something
Media analysis - 22Argument miningMining arguments, opinions and why they hold such an opinion
- 23NLP Structural approachGrammars, hand coded set of rules, linguistic stage
- 24NLP Statistical approachMachine learning, general learning algorithms, computational stage
- 25How does Statistical approach work?Training phase: input manually annotated text, finds features and remembers them
Testing phase: input unannotated text that is annotated with learned features - 26Results evaluationPrecision (found correct arguments), Recall (missed out argument), F score (proportion of precision and recall)
- 27NLP PipelineNotes
- 28Pro-argumentArguments for these claims, supports
Default inference, RA - 29Con-argumentArguments against these claims, attacks
Default Conflict, CA - 30Single argumentP (premise) points to C (conclusion)
- 31Linked argumentTwo premises share same RA box and support conclusion together
- 32Convergent argumentTwo premises to one conclusion
Support conclusion separately - 33Divergent argumentOne premise to two conclusions
- 34Serial argumentP point to Q which then point to C
Chain of reasoning - 35EnthymemesMissing elements, assumptions
We then need to transform the implicit premise/conclusion to explicit before we evaluate it - 36Walton's Argumentation schemesTypical patterns of informal reasoning
- 37Cause to effectGenerally, if A occurs, then B will occur
In this case, A occurs (or might occur)
Therefore, in this case, B will occur (or might occur) - 38AnalogyGenerally, case C1 is similar to C2
A is true (or false) for C1
Therefore, A is true (or false) for C2 - 39Position to knowA is in position to know whether P is true (or false)
A asserts that P is true (false)
Therefore, P is true (false) - 40PopularityIf a large majority accepts P as true, then there exists a (defeasible) presumption in favour of P
A majority accepts P as true
Therefore, there exists a presumption in favour of P - 41RebuttalConflicting with conclusion
A therefore B
But B conflicts with C - 42UnderminingConflicting with one of the premises
A therefore B
But A conflicts with C - 43Inference structurePropositional content
Logical and Arg theory - 44Illocutionary structuresIllocutionary connections
Speech act theory - 45Dialogue structuresTransitions
Dialectical theories and dialogue systems - 46Formal dialogue systemsDialogue games, set of rules regarding how players can discuss and exchange arguments
- 47Persuasion dialogue system (Prakken 2005)● claim(p) then why(p), claim(not-p), concede(p)
● why(p) then argue(A), retract(p)
● argue(A) then why(p), concede(p); where p is prem(A)
● concede(p) then nomove
● retract(p) then nomove - 48Taxonomy of illocutions (Bach and Harnish 1979)1. assertives: S's belief o e.g. claiming, conceding, testifying, deducing, arguing, denying, criticizing, rebutting
2. directives: S's desire about a possible future H's act o e.g. asking, commending, requesting, advising
3. commissives: S's intention to do something o e.g. promising, threatening, offering
4. acknowledgments: feelings toward H o e.g. apologizing, congratulating, thanking - 49Constitutive rules (Searle 1969)1. Propositional content rules ● some illocutions can only be achieved with an appropriate propositional content ● e.g. a promise may refer only to what is in the future and under the control of a speaker
2. Preparatory rules ● determine what a speaker presupposes in performing a speech act ● e.g. a speaker cannot marry a couple unless he is legally authorized to do so
3. Sincerity rules ● tell what psychological state is expressed ● e.g. an assertion expresses belief, a promise expresses an intention to do something ● a speech act is sincere only if a speaker is actually in this state
4. Essential rules ● determine what a speech act consists in essentially ● e.g. a promise commits a speaker to perform an act expressed in a propositional content - 50Locutions and locution nodesA locution node contains an Argumentative Discourse Unit (ADU) preceded by the speaker's identification
A locution (typically) has ONE propositional content
Ellipsis, pronominalisation, etc., should not be reconstructed in the ADU (which should be simply a span of the original discourse material as uttered)
Locutions appear on the right-hand side of an IAT analysis - 51Illocutionary connections (ICs) and illocutionary forcesICs link locutions (right-hand side) to propositional contents (left-hand side) They are based on the concept of illocutionary force introduced by speech act theory (see e.g. Searle 1969, Searle and Vanderveken 1985)
Typically, one locution has one illocutionary connection
Examples of illocutionary forces: asserting, questioning, offering, declaring, testifying, etc. - 52Illocutionary connections anchored in locutions/
- 53Asserting (A)The speaker S is asserting p to communicate his opinion on p
- 54Questioning (Q)S is questioning whether p when S formulates p as interrogative sentence of the form using a Yes/No question or a Wh-question Pure Questioning (PQ), Assertive Questioning (AQ), and Rhetorical Questioning (RQ)
- 55Challenging (Ch)When S is challenging p, S declares that he is seeking (asking about) the grounds for H's opinion on p. Pure Challenging (PCh), Assertive Challenging (ACh), Rhetorical Challenging (RCh)
- 56Popular Conceding (PCn)In popular concession, the speaker communicates some sort of general knowledge which is taken to be obvious and as such does not require to be defended
- 57Illocutionary connections anchored in transitionsThey link transitions (right-hand side) to propositional relations or propositional contents (left-hand side)
Typically, one transition has one illocutionary connection - 58Agreeing (Agr)is used for expressing a positive reaction, i.e. when the speaker S declares that they share the opinion of the interlocutor. This can take the basic form of signalling such as "Yes", "Indeed", "Most definitely", "Sure", but may as well be a complete sentence. Agreeing takes as a content a propositional content
- 59Disagreeing (Disagr)is used for expressing a negative reaction, i.e. when S declares not to share the interlocutor's opinion. This can take the form of utterances which have similar meaning to "No" (e.g. "I'm not saying that", "Actually, that's not correct", "Definitely not", "No, it's not") or it can be an utterance with a complete propositional content. Disagreeing takes as a content a relation of conflict (i.e. a CA)
- 60Arguing (Arg)S is arguing when he defends a standpoint. Arguing takes as a content a relation of inference (i.e. an RA)
- 61Default IllocutingIf an illocutionary connection does not match the guidelines for any IC described above, then it can be labelled Default Illocuting. This illocutionary connection is also currently used to connect an MA to its TA anchor when the MA is being used to answer a question
- 62Reported speechIt holds when one speaker reports what another speaker said.
The original locution contains the text as it was said (i.e., direct quotation).
This is not a type of Illocutionary connection. - 63RephraseIt holds between two propositions when one proposition is used to rephrase, restate or reformulate another proposition. ● Different propositions connected through a variety of different relation: Specialisation, Generalisation, Instantiation, etc. ● Rephrasing is not repeating. ● Question answering: It often involves rephrasing because the propositional content of a question is stereotypically instantiated, resolved, or refined by its answer. ● Rephrase is always structurally the same: one incoming edge and one outgoing edge. ● Different to inference relationships
- 64RepetitionIt involves multiple utterances with the same propositional content
This is not a type of Illocutionary Connection - 65What are the goals of Argumentation?To identify, analyse and evaluate (determining if the argument is weak or strong) and invent (form new conclusions) arguments
- 66How do you define an argument?Argument refers to the giving of reasons to support or criticise a claim that is questionable or open to doubt
It is a set of statements, made of three parts (set of premises, conclusion, inference from the premise to conclusion) - 67Deductive argumentGeneral premises are used to form a specific conclusion
- 68Inductive argumentHow probable it is to happen?
- 69Presumptive argumentHow plausible is it to happen?
- 70FallacyReason why the argument fails, errors of reasoning
- 71Practical reasoningReasoning we commonly use to decide on which course of action to take, does not follow a pattern
- 72Argument diagramIs an box and arrow presentation of an argument where boxes represent premises/conclusions/propositions and arrows inferences
- 73ArgumentationIs a chain of arguments, where the conclusion of one inference is a premise in the next one
Informal reasoning, pro- and con- arguments - 74Three ways to attack an argument1. By doubting acceptability
2. By questioning premise
3. With a counter-argument - 75OVAOnline Visualisation of Argument
- 76What is Argument Web's goal?To improve the quality of online argument and debate
Informações
- Descrição
- Argumentation and Computing (Argumentation) FlashCards sobre Argumentation Theory, criado por Neja Cesnik em 30-04-2018.
- Criado por
- Neja Cesnik
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