Recognizing Reputation Defence Strategies in Critical Political Exchanges

Naderi, Nona; Hirst, Graeme

doi:10.26615/978-954-452-049-6_069

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…Previous studies on face-saving and reputation management focused on identifying various persuasive strategies and their effectiveness (Benoit, 1995;Coombs and Holladay, 2008;Burns and Bruner, 2000;Sheldon and Sallot, 2008). In the NLP field, Naderi and Hirst (2017) performed a manual annotation analysis on reputation defence strategies in Parliament and proposed a computational model to identify strategies of denial, excuse, justification, and concession. Naderi and Hirst (2018) further proposed two approaches to automatically annotate unlabeled speeches with defence strategies.…”

Section: Related Workmentioning

confidence: 99%

Using context to identify the language of face-saving

Naderi

Hirst

2018

Proceedings of the 5th Workshop on Argument Mining

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We created a corpus of utterances that attempt to save face from parliamentary debates and use it to automatically analyze the language of reputation defence. Our proposed model that incorporates information regarding threats to reputation can predict reputation defence language with high confidence. Further experiments and evaluations on different datasets show that the model is able to generalize to new utterances and can predict the language of reputation defence in a new dataset.

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Section: Related Workmentioning

confidence: 99%

Using context to identify the language of face-saving

Naderi

Hirst

2018

Proceedings of the 5th Workshop on Argument Mining

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A Deep Modular RNN Approach for Ethos Mining

Duthie

Budzyńska

2018

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence

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Automatically recognising and extracting the reasoning expressed in natural language text is extremely demanding and only very recently has there been significant headway. While such argument mining focuses on logos (the content of what is said) evidence has demonstrated that using ethos (the character of the speaker) can sometimes be an even more powerful tool of influence. We study the UK parliamentary debates which furnish a rich source of ethos with linguistic material signalling the ethotic relationships between politicians. We then develop a novel deep modular recurrent neural network, DMRNN, approach and employ proven methods from argument mining and sentiment analysis to create an ethos mining pipeline. Annotation of ethotic statements is reliable and its extraction is robust (macro-F1 = 0.83), while annotation of polarity is perfect and its extraction is solid (macro-F1 = 0.84). By exploring correspondences between ethos in political discourse and major events in the political landscape through ethos analytics, we uncover tantalising evidence that identifying expressions of positive and negative ethotic sentiment is a powerful instrument for understanding the dynamics of governments.

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Design and Implementation of Medical QA System using Machine Learning Techniques

Patil

Sambrekar

2021

IJSRCSEIT

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Nowadays, people rely on Traditional books or Google for every answer to their questions on a day-to-day basis, from basic information to medical queries. Till now, people are facing problems and are unable to find the accurate answer to their questions or fetch relevant results. Also, this technique is time-consuming as people have to go through many books to obtain one relevant answer or search various websites, which is a tedious task and not an efficient way in today's world where time is the top priority, yet the majority of people follow these techniques. So, to overcome this technique and solve the current problems, we have implemented a new technique in this paper. The BERT model, pre-trains deep bidirectional representations from the unlabeled text which conditions on both left and right, as a result, provides accurate answers to the user’s query when compared to the state-of-the-art model. This same model can be further implemented in other domains to obtain accurate results.

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Recognizing Reputation Defence Strategies in Critical Political Exchanges

Cited by 3 publications

References 14 publications

Using context to identify the language of face-saving

Using context to identify the language of face-saving

A Deep Modular RNN Approach for Ethos Mining

Design and Implementation of Medical QA System using Machine Learning Techniques

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