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Winning on the Merits: The Joint Effects of Content and Style on Debate Outcomes

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TLDR
A predictive model of debate is proposed that estimates the effects of linguistic features and the latent persuasive strengths of different topics, as well as the interactions between the two, and finds that winning sides employ stronger arguments.
Abstract
Debate and deliberation play essential roles in politics and government, but most models presume that debates are won mainly via superior style or agenda control Ideally, however, debates would be won on the merits, as a function of which side has the stronger arguments We propose a predictive model of debate that estimates the effects of linguistic features and the latent persuasive strengths of different topics, as well as the interactions between the two Using a dataset of 118 Oxford-style debates, our model's combination of content (as latent topics) and style (as linguistic features) allows us to predict audience-adjudicated winners with 74% accuracy, significantly outperforming linguistic features alone (66%) Our model finds that winning sides employ stronger arguments, and allows us to identify the linguistic features associated with strong or weak arguments

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Proceedings ArticleDOI

Argument Generation with Retrieval, Planning, and Realization

TL;DR: This paper presents a novel framework, CANDELA, which consists of a powerful retrieval system and a novel two-step generation model, where a text planning decoder first decides on the main talking points and a proper language style for each sentence, then a content realization decoder reflects the decisions and constructs an informative paragraph-level argument.
Proceedings ArticleDOI

Neural Argument Generation Augmented with Externally Retrieved Evidence

TL;DR: This article proposed an encoder-decoder style neural network-based argument generation model enriched with externally retrieved evidence from Wikipedia, which generates a set of talking point phrases as intermediate representation, followed by a separate decoder producing the final argument based on both input and the keyphrases.
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Persuasive Influence Detection: The Role of Argument Sequencing.

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Automatic Essay Scoring Incorporating Rating Schema via Reinforcement Learning

TL;DR: A reinforcement learning framework for essay scoring that incorporates quadratic weighted kappa as guidance to optimize the scoring system and experiment results show the effectiveness of this framework.
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Trouble on the Horizon: Forecasting the Derailment of Online Conversations as they Develop

TL;DR: This work introduces a conversational forecasting model that learns an unsupervised representation of conversational dynamics and exploits it to predict future derailment as the conversation develops, and shows that it outperforms state-of-the-art systems at forecasting derailment.
References
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Book

The Theory of Communicative Action

TL;DR: In this article, an apex seal for a rotary combustion engine is disclosed having a hollow, thin wall, tubular, metal core member embedded in an extruded composite metal-carbon matrix, adapted to slideably engage the slot of the rotor in which it rides and sealingly engage the rotor housing against which it is spring and gas pressure biased.
Proceedings Article

Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

TL;DR: A Sentiment Treebank that includes fine grained sentiment labels for 215,154 phrases in the parse trees of 11,855 sentences and presents new challenges for sentiment compositionality, and introduces the Recursive Neural Tensor Network.
Proceedings ArticleDOI

Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis

TL;DR: A new approach to phrase-level sentiment analysis is presented that first determines whether an expression is neutral or polar and then disambiguates the polarity of the polar expressions.
Proceedings ArticleDOI

Accurate Unlexicalized Parsing

TL;DR: It is demonstrated that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar.
Journal ArticleDOI

The theory of communicative action

TL;DR: Habermas and Communicative Action as mentioned in this paper The Theory of Communicative Actions is a generalization of the theory of communicative action, which was introduced by Jürgen Habermas.
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