Abstract image of a woman sitting on books and studying on a laptop

Argument Mining

Download as PPTX, PDF
I
ivaderivader

This document summarizes research presented at recent Argument Mining workshops. It describes tasks from 2021 and 2022 on key point analysis and validity-novelty prediction. It also outlines papers on extracting argument components, predicting reasoning markers, and detecting argument boundaries. The document indicates that argument mining can analyze debates on social media and that legal corpora can help develop argument mining systems.

Technology
1 of 17
Download to read offline
1
2
Most read
3
4
Most read
5
6
7
8
9
10
11
12
13
14
15
16
17
Argument Mining 2023.08.01
Contents • Argument Mining • Workshop on Argument Mining  Argument Mining Procedure  2021 Task : Key Point Analysis  2022 Task : Validity-Novelty Prediction  Other papars • Development of Argument Mining
2 Argument Mining [1] Chen et al., “Analyzing Culture-Specific Argument Structures in Learner Essays,” ACL ArgMining 2022 [2] Nguyen et al., “Extracting Argument and Domain Words for Identifying Argument Components in Texts,” ACL ArgMining 2015 • What is Argument Mining?
3 Argument Mining [1] Stab et al., “Parsing Argumentation Structures in Persuasive Essays” ACL’17 • Argumentation Structures
4 Argument Mining [1] Sofi et al., “A Robustness Evaluation Framework for Argument Mining” ACL ArgMining 2022 • Argument Mining
5 Argument Mining Workshop [1] Nguyen et al., “Extracting Argument and Domain Words for Identifying Argument Components in Texts” ACL ArgMining 2015 • Nguyen et al., “Extracting Argument and Domain Words for Identifying Argument Components in Texts,” ACL ArgMining 2015 LDA : To learn argument and domain words • Lexical aspect : topic model  development data (described below) to separate argument words (e.g. ‘view’, ‘conclude’, ‘think’) from domain words (e.g. ‘art’, ‘life’) <-> n-gram • Structural aspect : subject and main verb  use dependency parses to extract pairs of subject and main verb of sentences, e.g. “I.think”, “view.be”
6 Argument Mining Workshop [1] Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022 • Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022
7 Argument Mining Workshop [1] Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022 • Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022 Reasoning Marker Prediction Argument Component Input AC types: “[premise] premise text [RM] [claim] claim text“ RMs such as “in conclusion" are very common in the dataset before major claims.
8 Argument Mining 2021 Task [1] Alshomary et al., “Key Point Analysis via Contrastive Learning and Extractive Argument Summarization” ACL ArgMining 2021 • KPA(Key Point Analysis) : Key Point Analysis (KPA) is a new NLP task, with strong relations to Computational Argumentation, Opinion Analysis, and Summarization
9 Workshop on Argument Mining 2021 [1] Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021 • Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021 contribution : It is possible to distinguish between arguments and reasons for short articles such as Twitter. Public opinion on the SNS becomes clear. • Support with reason  : support the claim • Support without reason  : support the claim. But not provide a reason • No explicit support  :the user has a neutral or unclear stance
10 Workshop on Argument Mining 2021 [1] Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021 • Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021
11 Argument Mining 2022 Task [1] Heinisch et al., “Data Augmentation for Improving the Prediction of Validity and Novelty of Argumentative Conclusions” ACL ArgMining 2022 • PREDICTING THE VALIDITY AND NOVELTY OF ARGUMENTS
12 Workshop on Argument Mining 2022 [1] Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022 • Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022 Contribution : Clearly Argumentation which context unit aspects should be considered for categorization of arguments (token, chunked, and sentence-level) • Sequence Tagging  Named Entity Recognition(NER) • Chunk Normalization  Syntactic Chunker • Multi-Class Chunk Classification  Entire Chunk, separated with [SEP] token • Sentence Classification
13 Workshop on Argument Mining 2022 [1] Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022 • Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022
14 Argument Mining Workshop [1] Poudyal et al., “ECHR: Legal Corpus for Argument Mining” ACL ArgMining 2020 • Poudyal et al., “ECHR: Legal Corpus for Argument Mining” ACL ArgMining 2020 Proceed with Argument Mining using BERT The learning process is the same as before Provide visualization tools in user text -> Efficient understanding of Argument
15 Development of Argument Mining [1] https://argmining-org.github.io/2023/ • Argument Mining 2023 Task
Argument Mining

More Related Content

DOCX
bồn tắm jacuzzi.docx
DarosVitNam
 
PDF
Argument Annotation And Analysis Using Deep Learning With Attention Mechanism...
Stephen Faucher
 
PPTX
Envisioning argumentation and decision making support for debates in open onl...
jodischneider
 
PPTX
Argumentation mining--an introduction for linguists--Fribourg--2019-09-02
jodischneider
 
PPTX
An informatics perspective on argumentation mining - SICSA 2014-07-09
jodischneider
 
PDF
UKSG webinar - Introduction to Text-Mining Research Papers with Petr Knoth an...
UKSG: connecting the knowledge community
 
PDF
NCCU: The Story of Data Science and Machine Learning Workshop - Political Blo...
The Statistical and Applied Mathematical Sciences Institute
 
PDF
Mining Arguments from Online Debating Systems
Andrea Pazienza
 
bồn tắm jacuzzi.docx
DarosVitNam
 
Argument Annotation And Analysis Using Deep Learning With Attention Mechanism...
Stephen Faucher
 
Envisioning argumentation and decision making support for debates in open onl...
jodischneider
 
Argumentation mining--an introduction for linguists--Fribourg--2019-09-02
jodischneider
 
An informatics perspective on argumentation mining - SICSA 2014-07-09
jodischneider
 
UKSG webinar - Introduction to Text-Mining Research Papers with Petr Knoth an...
UKSG: connecting the knowledge community
 
NCCU: The Story of Data Science and Machine Learning Workshop - Political Blo...
The Statistical and Applied Mathematical Sciences Institute
 
Mining Arguments from Online Debating Systems
Andrea Pazienza
 

More from ivaderivader (20)

PPTX
Papers at CHI23
ivaderivader
 
PPTX
DDGK: Learning Graph Representations for Deep Divergence Graph Kernels
ivaderivader
 
PPTX
So Predictable! Continuous 3D Hand Trajectory Prediction in Virtual Reality
ivaderivader
 
PPTX
Reinforcement Learning-based Placement of Charging Stations in Urban Road Net...
ivaderivader
 
PPTX
Prediction for Retrospection: Integrating Algorithmic Stress Prediction into ...
ivaderivader
 
PPTX
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Orien...
ivaderivader
 
PPTX
A Style-Based Generator Architecture for Generative Adversarial Networks
ivaderivader
 
PPTX
CatchLIve: Real-time Summarization of Live Streams with Stream Content and In...
ivaderivader
 
PPTX
Perception! Immersion! Empowerment! Superpowers as Inspiration for Visualization
ivaderivader
 
PPTX
Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic F...
ivaderivader
 
PPTX
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling
ivaderivader
 
PPTX
StoryMap: Using Social Modeling and Self-Modeling to Support Physical Activit...
ivaderivader
 
PPTX
Bad Breakdowns, Useful Seams, and Face Slapping: Analysis of VR Fails on YouTube
ivaderivader
 
PPTX
Invertible Denoising Network: A Light Solution for Real Noise Removal
ivaderivader
 
PPTX
Traffic Demand Prediction Based Dynamic Transition Convolutional Neural Network
ivaderivader
 
PPTX
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training
ivaderivader
 
PPTX
Screen2Vec: Semantic Embedding of GUI Screens and GUI Components
ivaderivader
 
PPTX
Augmenting Decisions of Taxi Drivers through Reinforcement Learning for Impro...
ivaderivader
 
PPTX
Natural Language to Visualization by Neural Machine Translation
ivaderivader
 
PPTX
Recommending What Video to Watch Next: A Multitask Ranking System
ivaderivader
 
Papers at CHI23
ivaderivader
 
DDGK: Learning Graph Representations for Deep Divergence Graph Kernels
ivaderivader
 
So Predictable! Continuous 3D Hand Trajectory Prediction in Virtual Reality
ivaderivader
 
Reinforcement Learning-based Placement of Charging Stations in Urban Road Net...
ivaderivader
 
Prediction for Retrospection: Integrating Algorithmic Stress Prediction into ...
ivaderivader
 
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Orien...
ivaderivader
 
A Style-Based Generator Architecture for Generative Adversarial Networks
ivaderivader
 
CatchLIve: Real-time Summarization of Live Streams with Stream Content and In...
ivaderivader
 
Perception! Immersion! Empowerment! Superpowers as Inspiration for Visualization
ivaderivader
 
Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic F...
ivaderivader
 
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling
ivaderivader
 
StoryMap: Using Social Modeling and Self-Modeling to Support Physical Activit...
ivaderivader
 
Bad Breakdowns, Useful Seams, and Face Slapping: Analysis of VR Fails on YouTube
ivaderivader
 
Invertible Denoising Network: A Light Solution for Real Noise Removal
ivaderivader
 
Traffic Demand Prediction Based Dynamic Transition Convolutional Neural Network
ivaderivader
 
MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training
ivaderivader
 
Screen2Vec: Semantic Embedding of GUI Screens and GUI Components
ivaderivader
 
Augmenting Decisions of Taxi Drivers through Reinforcement Learning for Impro...
ivaderivader
 
Natural Language to Visualization by Neural Machine Translation
ivaderivader
 
Recommending What Video to Watch Next: A Multitask Ranking System
ivaderivader
 
Ad

Recently uploaded (20)

PPT
Module 1.ppt Iot fundamentals and Architecture
nanditha7766
 
PDF
STKI Israel Market Study 2025 version august
Dr. Jimmy Schwarzkopf
 
PDF
The influence of sentiment analysis in enhancing early warning system model f...
IAESIJAI
 
PPTX
2018-HIPAA-Renewal-Training for executives
Mayank Mathur
 
PPT
Geologic Time for studying geology for geologist
ssuser738f5a
 
PDF
How ambidextrous entrepreneurial leaders react to the artificial intelligence...
IAESIJAI
 
PPTX
Chapter 5: Probability Theory and Statistics
RandyFin
 
PPTX
Configure Apache Mutual Authentication
Antonino Piraino
 
PPTX
Final SEM Unit 1 for mit wpu at pune .pptx
anishtilekar08
 
PDF
From MVP to Full-Scale Product A Startup’s Software Journey.pdf
KodekX
 
PDF
A contest of sentiment analysis: k-nearest neighbor versus neural network
IAESIJAI
 
PDF
Getting started with AI Agents and Multi-Agent Systems
Maxim Salnikov
 
PDF
Credit Without Borders: AI and Financial Inclusion in Bangladesh
Ehsan Tanim
 
PDF
CloudStack 4.21: First Look Webinar slides
ShapeBlue
 
PDF
ENT215_Completing-a-large-scale-migration-and-modernization-with-AWS.pdf
ssuser28425f
 
PPTX
Benefits of Physical activity for teenagers.pptx
Nokwanda Thabethe
 
PDF
A proposed approach for plagiarism detection in Myanmar Unicode text
IAESIJAI
 
PDF
Convolutional neural network based encoder-decoder for efficient real-time ob...
IAESIJAI
 
PDF
Hybrid horned lizard optimization algorithm-aquila optimizer for DC motor
IAESIJAI
 
PDF
A review of recent deep learning applications in wood surface defect identifi...
IAESIJAI
 
Module 1.ppt Iot fundamentals and Architecture
nanditha7766
 
STKI Israel Market Study 2025 version august
Dr. Jimmy Schwarzkopf
 
The influence of sentiment analysis in enhancing early warning system model f...
IAESIJAI
 
2018-HIPAA-Renewal-Training for executives
Mayank Mathur
 
Geologic Time for studying geology for geologist
ssuser738f5a
 
How ambidextrous entrepreneurial leaders react to the artificial intelligence...
IAESIJAI
 
Chapter 5: Probability Theory and Statistics
RandyFin
 
Configure Apache Mutual Authentication
Antonino Piraino
 
Final SEM Unit 1 for mit wpu at pune .pptx
anishtilekar08
 
From MVP to Full-Scale Product A Startup’s Software Journey.pdf
KodekX
 
A contest of sentiment analysis: k-nearest neighbor versus neural network
IAESIJAI
 
Getting started with AI Agents and Multi-Agent Systems
Maxim Salnikov
 
Credit Without Borders: AI and Financial Inclusion in Bangladesh
Ehsan Tanim
 
CloudStack 4.21: First Look Webinar slides
ShapeBlue
 
ENT215_Completing-a-large-scale-migration-and-modernization-with-AWS.pdf
ssuser28425f
 
Benefits of Physical activity for teenagers.pptx
Nokwanda Thabethe
 
A proposed approach for plagiarism detection in Myanmar Unicode text
IAESIJAI
 
Convolutional neural network based encoder-decoder for efficient real-time ob...
IAESIJAI
 
Hybrid horned lizard optimization algorithm-aquila optimizer for DC motor
IAESIJAI
 
A review of recent deep learning applications in wood surface defect identifi...
IAESIJAI
 
Ad

Argument Mining

  • 2. Contents • Argument Mining • Workshop on Argument Mining  Argument Mining Procedure  2021 Task : Key Point Analysis  2022 Task : Validity-Novelty Prediction  Other papars • Development of Argument Mining
  • 3. 2 Argument Mining [1] Chen et al., “Analyzing Culture-Specific Argument Structures in Learner Essays,” ACL ArgMining 2022 [2] Nguyen et al., “Extracting Argument and Domain Words for Identifying Argument Components in Texts,” ACL ArgMining 2015 • What is Argument Mining?
  • 4. 3 Argument Mining [1] Stab et al., “Parsing Argumentation Structures in Persuasive Essays” ACL’17 • Argumentation Structures
  • 5. 4 Argument Mining [1] Sofi et al., “A Robustness Evaluation Framework for Argument Mining” ACL ArgMining 2022 • Argument Mining
  • 6. 5 Argument Mining Workshop [1] Nguyen et al., “Extracting Argument and Domain Words for Identifying Argument Components in Texts” ACL ArgMining 2015 • Nguyen et al., “Extracting Argument and Domain Words for Identifying Argument Components in Texts,” ACL ArgMining 2015 LDA : To learn argument and domain words • Lexical aspect : topic model  development data (described below) to separate argument words (e.g. ‘view’, ‘conclude’, ‘think’) from domain words (e.g. ‘art’, ‘life’) <-> n-gram • Structural aspect : subject and main verb  use dependency parses to extract pairs of subject and main verb of sentences, e.g. “I.think”, “view.be”
  • 7. 6 Argument Mining Workshop [1] Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022 • Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022
  • 8. 7 Argument Mining Workshop [1] Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022 • Clayton et al., “Predicting the Presence of Reasoning Markers in Argumentative Text” ACL ArgMining 2022 Reasoning Marker Prediction Argument Component Input AC types: “[premise] premise text [RM] [claim] claim text“ RMs such as “in conclusion" are very common in the dataset before major claims.
  • 9. 8 Argument Mining 2021 Task [1] Alshomary et al., “Key Point Analysis via Contrastive Learning and Extractive Argument Summarization” ACL ArgMining 2021 • KPA(Key Point Analysis) : Key Point Analysis (KPA) is a new NLP task, with strong relations to Computational Argumentation, Opinion Analysis, and Summarization
  • 10. 9 Workshop on Argument Mining 2021 [1] Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021 • Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021 contribution : It is possible to distinguish between arguments and reasons for short articles such as Twitter. Public opinion on the SNS becomes clear. • Support with reason  : support the claim • Support without reason  : support the claim. But not provide a reason • No explicit support  :the user has a neutral or unclear stance
  • 11. 10 Workshop on Argument Mining 2021 [1] Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021 • Bhatti et al., “Argument Mining on Twitter: A Case Study on the Planned Parenthood Debate” ACL ArgMining 2021
  • 12. 11 Argument Mining 2022 Task [1] Heinisch et al., “Data Augmentation for Improving the Prediction of Validity and Novelty of Argumentative Conclusions” ACL ArgMining 2022 • PREDICTING THE VALIDITY AND NOVELTY OF ARGUMENTS
  • 13. 12 Workshop on Argument Mining 2022 [1] Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022 • Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022 Contribution : Clearly Argumentation which context unit aspects should be considered for categorization of arguments (token, chunked, and sentence-level) • Sequence Tagging  Named Entity Recognition(NER) • Chunk Normalization  Syntactic Chunker • Multi-Class Chunk Classification  Entire Chunk, separated with [SEP] token • Sentence Classification
  • 14. 13 Workshop on Argument Mining 2022 [1] Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022 • Ruckdeschel et al. “Boundary Detection and Categorization of Argument Aspects via Supervised Learning” ArgMining 2022
  • 15. 14 Argument Mining Workshop [1] Poudyal et al., “ECHR: Legal Corpus for Argument Mining” ACL ArgMining 2020 • Poudyal et al., “ECHR: Legal Corpus for Argument Mining” ACL ArgMining 2020 Proceed with Argument Mining using BERT The learning process is the same as before Provide visualization tools in user text -> Efficient understanding of Argument
  • 16. 15 Development of Argument Mining [1] https://argmining-org.github.io/2023/ • Argument Mining 2023 Task