# Conversational Analysis of Daily Dialog Data using Polite Emotional Dialogue Acts

arXiv: https://arxiv.org/abs/2205.02921 · HTML: https://mlsanity.com/paper/2205.02921/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 28 references that are in the map.
- First posted on arXiv 5 May 2022.

## Builds on (most cited first, 11 of 11)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset](https://mlsanity.com/paper/1710.03957/) (2017)
- [A Computational Approach to Politeness with Application to Social Factors](https://mlsanity.com/paper/1306.6078/) (2013)
- [Conversations Gone Alright: Quantifying and Predicting Prosocial Outcomes in Online Conversations](https://mlsanity.com/paper/2102.08368/) (2021)
- [Interpreting Neural Networks to Improve Politeness Comprehension](https://mlsanity.com/paper/1610.02683/) (2016)
- [EDA: Enriching Emotional Dialogue Acts using an Ensemble of Neural Annotators](https://mlsanity.com/paper/1912.00819/) (2019)
- [Towards Dialogue-based Navigation with Multivariate Adaptation driven by Intention and Politeness for Social Robots](https://mlsanity.com/paper/1809.07269/) (2018)
- [GradAscent at EmoInt-2017: Character- and Word-Level Recurrent Neural Network Models for Tweet Emotion Intensity Detection](https://mlsanity.com/paper/1803.11509/) (2018)
- [Conversational Analysis using Utterance-level Attention-based Bidirectional Recurrent Neural Networks](https://mlsanity.com/paper/1805.06242/) (2018)
- [Discourse-Wizard: Discovering Deep Discourse Structure in your Conversation with RNNs](https://mlsanity.com/paper/1806.11420/) (2018)
- [Exploratory evaluation of politeness in human-robot interaction](https://mlsanity.com/paper/2103.08441/) (2021)

## Built on by (most cited first, 1 of 1)

- [Computational Politeness in Natural Language Processing: A Survey](https://mlsanity.com/paper/2407.12814/) (2024)

## Abstract (arXiv)

Many socio-linguistic cues are used in conversational analysis, such as emotion, sentiment, and dialogue acts. One of the fundamental cues is politeness, which linguistically possesses properties such as social manners useful in conversational analysis. This article presents findings of polite emotional dialogue act associations, where we can correlate the relationships between the socio-linguistic cues. We confirm our hypothesis that the utterances with the emotion classes Anger and Disgust are more likely to be impolite. At the same time, Happiness and Sadness are more likely to be polite. A less expectable phenomenon occurs with dialogue acts Inform and Commissive which contain more polite utterances than Question and Directive. Finally, we conclude on the future work of these findings to extend the learning of social behaviours using politeness.