CAISA at WASSA 2022: Adapter-Tuning for Empathy Prediction

Lahnala, Allison; Welch, Charles; Flek, Lucie

doi:10.18653/v1/2022.wassa-1.31

Cited by 3 publications

(4 citation statements)

References 20 publications

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“…Most relevant to our work are recent advances in social and emotional commonsense reasoning using using language models. Specifically, prior methods have used finetuning of language models such as BERT (Devlin et al, 2019;Reimers and Gurevych, 2019) and GPT-2 (Radford et al) to model events and the emotional reactions caused by everyday events (Rashkin et al, , 2018Sap et al, 2019b;Bosselut et al, 2019;Wang et al, 2022;West et al, 2022;Mostafazadeh et al, 2020) as well as predicting empathy, condolence, or prosocial outcomes (Lahnala et al, 2022a;Kumano et al;Boukricha et al, 2013;Zhou and Jurgens, 2020;Bao et al, 2021). Understanding the emotional reactions elicited by events is a challenging task for many NLP systems, as it requires commonsense knowledge and extrapolation of meanings beyond the text alone.…”

Section: Related Workmentioning

confidence: 99%

Modeling Empathic Similarity in Personal Narratives

Shen,

Sap,

Colon-Hernandez

et al. 2023

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

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The most meaningful connections between people are often fostered through expression of shared vulnerability and emotional experiences in personal narratives. We introduce a new task of identifying similarity in personal stories based on empathic resonance, i.e., the extent to which two people empathize with each others' experiences, as opposed to raw semantic or lexical similarity, as has predominantly been studied in NLP. Using insights from social psychology, we craft a framework that operationalizes empathic similarity in terms of three key features of stories: main events, emotional trajectories, and overall morals or takeaways. We create EM-PATHICSTORIES, a dataset of 1,500 personal stories annotated with our empathic similarity features, and 2,000 pairs of stories annotated with empathic similarity scores. Using our dataset, we finetune a model to compute empathic similarity of story pairs, and show that this outperforms semantic similarity models on automated correlation and retrieval metrics. Through a user study with 150 participants, we also assess the effect our model has on retrieving stories that users empathize with, compared to naive semantic similarity-based retrieval, and find that participants empathized significantly more with stories retrieved by our model. Our work has strong implications for the use of empathy-aware models to foster human connection and empathy between people.

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Section: Related Workmentioning

confidence: 99%

Modeling Empathic Similarity in Personal Narratives

Shen,

Sap,

Colon-Hernandez

et al. 2023

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

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“…In this approach, a dataset of labeled dialogues is used to train a model. This approach has been used in several studies (Bentis, 2021), (Buechel et al, 2018), (Chen et al, 2022), (Lahnala et al, 2022) and (Hosseini and Caragea, 2021). Another evaluation technique is the to detect the emotions expressed in dialogue.…”

Section: Related Workmentioning

confidence: 99%

“…Other studies have focused on the use of deep learning techniques, such as recurrent neural networks (RNNs) and transformer models, to predict empathy in text. These approaches have shown promising results, with some studies reporting high levels of accuracy in empathy prediction (Chen et al, 2022), (Lahnala et al, 2022) and (Hosseini and Caragea, 2021).…”

Section: Introductionmentioning

confidence: 99%

EMP-EVAL: A Framework for Measuring Empathy in Open Domain Dialogues

Amjad¹,

Zeeshan²,

Beg³

2023

Preprint

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Measuring empathy in conversation can be challenging, as empathy is a complex and multifaceted psychological construct that involves both cognitive and emotional components. Human evaluations can be subjective, leading to inconsistent results. Therefore, there is a need for an automatic method for measuring empathy that reduces the need for human evaluations. In this paper, we proposed a novel approach EMP-EVAL, a simple yet effective automatic empathy evaluation method. The proposed technique takes the influence of Emotion, Cognitive and Emotional empathy. To the best knowledge, our work is the first to systematically measure empathy without the humanannotated provided scores. Experimental results demonstrate that our metrics can correlate with human preference, achieving comparable results with human judgments.

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“…The significance of data in this context cannot be overstated; it plays a pivotal role in shaping a model's ability to comprehend nuances, contextual information, and idiomatic expressions specific to a particular language [6]. Additionally, fine-tuning data must accurately mirror the linguistic intricacies and cultural nuances of the target language [7]. For languages with unique linguistic characteristics and cultural contexts [8], such as Vietnamese, acquiring suitable data becomes a formidable challenge.…”

Section: Introductionmentioning

confidence: 99%

A study on factors affecting the decision of choosing university of high school pupils in Quang Ngai province

Nguyen¹

2021

VMOST

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In fact, choosing a career and a university of high school pupils is very important. This study aims at identifying and measuring the factors affecting the decision of choosing a university of high school pupils in Quang Ngai province. The data of this study were collected from 340 answer sheets of grade 12 pupils of 5 high schools in Quang Ngai province in the 2019-2020 school year. By using the quantitative analysis methods, it has been shown that 5 factors are affecting the decision of choosing a university of pupils in Quang Ngai province, in the order of high importance to low including (1) University reputation, (2) Communication, (3) Learning conditions, (4) Factor belongs to the pupils, (5) Individuals.

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CAISA at WASSA 2022: Adapter-Tuning for Empathy Prediction

Cited by 3 publications

References 20 publications

Modeling Empathic Similarity in Personal Narratives

Modeling Empathic Similarity in Personal Narratives

EMP-EVAL: A Framework for Measuring Empathy in Open Domain Dialogues

A study on factors affecting the decision of choosing university of high school pupils in Quang Ngai province

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