Exploring Coping Strategies in Emotional Responses: A Role-Playing Corpus for Computational Analysis

Conceptos Básicos

Emotions are fundamentally linked to coping strategies that people use to deal with salient situations. This study introduces a novel corpus, COPING, to investigate how these coping strategies (attack, contact, distance, reject) are expressed in language and can be computationally identified.

Resumen

The study explores the relationship between emotions and coping strategies, a concept that has been underexplored in natural language processing (NLP) research. The authors follow psychological theories that treat emotions as episodes where people cope with events, and that influence their behavior through action tendencies.
To investigate this, the authors constructed the COPING corpus through a role-playing approach. Participants were asked to impersonate fictional characters representing different coping strategies (attack, contact, distance, reject) and respond to controversial scenarios on topics like abortion, immigration, and LGBTQ+ rights.
The analysis of the corpus shows that:

Participants were able to correctly associate the intended coping strategies with the corresponding emotional responses, aligning with psychological theories.
The textual expressions of coping strategies varied in their clarity, with attack and contact being more easily recognized by both human annotators and computational models compared to distance and reject.
Computational models, including fine-tuned language models and zero-shot classifiers, struggled to accurately identify the coping strategies expressed in the texts, suggesting that capturing these complex psychological constructs in language is a challenging task.
The study highlights the potential of using coping strategies to enhance emotion analysis in NLP, but also the difficulties in bridging psychological theories and computational approaches. The COPING corpus provides a valuable resource for further research in this direction.

Estadísticas

"I could not disagree more with your statement."
"I understand your perspective, but I feel that your ideas could have serious consequences."
"I'm sure you have your reasons, but I don't agree with your opinion on this topic."
"I'm not interested in your negative views. I'd rather not discuss this further."

Citas

"Emotions can be considered episodes where people cope with an event, and that influence their behavior through action tendencies."
"Essentially, emotions can be considered episodes where people cope with an event, and that influence their behavior through action tendencies."
"Theories of coping have great visibility in research on virtual agents and robotics due to their ability to model emotions at the behavioral level, but their potential for studying emotions in language (as a specific type of behavior) has not been fully explored so far."

Ideas clave extraídas de

Dealing with Controversy: An Emotion and Coping Strategy Corpus Based on Role Playing

by Enrica Troia... a las arxiv.org 10-01-2024

https://arxiv.org/pdf/2409.19025.pdf

Consultas más profundas

How can the insights from this study on coping strategies be applied to improve emotion analysis in other domains, such as customer service or mental health support?

The insights from the study on coping strategies can significantly enhance emotion analysis in various domains, particularly in customer service and mental health support. By understanding how individuals cope with emotional stimuli, organizations can tailor their responses to better meet the emotional needs of their clients.
In customer service, for instance, recognizing coping strategies such as "attack" or "contact" can help agents identify the emotional state of customers. If a customer expresses frustration (an emotion linked to the "attack" strategy), the agent can employ a more empathetic and solution-oriented approach, aiming to de-escalate the situation. Conversely, if a customer is expressing hope or relief (associated with the "contact" strategy), the agent can reinforce positive interactions, fostering a supportive environment.
In mental health support, the application of coping strategies can guide practitioners in understanding clients' emotional responses and coping mechanisms. By analyzing the language used by clients, therapists can identify underlying emotions and coping strategies, allowing for more personalized interventions. For example, if a client frequently uses language indicative of "distance" or "reject," therapists can explore these coping mechanisms further, helping clients develop healthier strategies for managing their emotions.
Overall, integrating coping strategy insights into emotion analysis can lead to more effective communication, improved emotional support, and enhanced client satisfaction across various domains.

What are the potential limitations of using role-playing to elicit coping strategies, and how could future studies address these limitations?

While role-playing is a valuable method for eliciting coping strategies, it does come with several limitations. One significant limitation is the artificial nature of the scenarios, which may not accurately reflect real-life emotional experiences. Participants may struggle to fully engage with the role they are playing, leading to responses that do not genuinely represent their coping strategies in authentic situations. Additionally, the reliance on participants' ability to understand and embody the coping strategies may introduce variability in the quality of the responses, as not all individuals may have the same level of acting skill or emotional insight.
To address these limitations, future studies could incorporate a mixed-methods approach that combines role-playing with real-life emotional experiences. For instance, researchers could gather data from individuals in naturalistic settings where they encounter emotionally charged situations, allowing for a more genuine expression of coping strategies. Furthermore, incorporating physiological measures (such as heart rate or galvanic skin response) could provide additional insights into participants' emotional states during role-playing, enhancing the validity of the findings.
Another approach could involve longitudinal studies that track individuals' coping strategies over time, providing a more comprehensive understanding of how these strategies evolve in response to different emotional stimuli. By addressing these limitations, future research can yield more robust and applicable insights into coping strategies and their expression in language.

Given the challenges in computational identification of coping strategies, how might interdisciplinary collaboration between psychology and NLP help advance the understanding of the relationship between language and emotional coping mechanisms?

Interdisciplinary collaboration between psychology and natural language processing (NLP) holds great potential for advancing the understanding of the relationship between language and emotional coping mechanisms. By combining psychological theories of emotion and coping with computational techniques, researchers can develop more nuanced models that capture the complexity of human emotional expression.
Psychologists can provide valuable insights into the theoretical frameworks that underpin coping strategies, such as Roseman's taxonomy, which links specific emotions to corresponding coping behaviors. This foundational knowledge can inform the development of NLP models that are better equipped to recognize and classify coping strategies in text. For instance, understanding the contextual factors that influence emotional responses can help NLP systems identify subtle linguistic cues that indicate coping mechanisms.
Conversely, NLP can enhance psychological research by enabling the analysis of large datasets of textual interactions, such as social media posts or customer service transcripts. This analysis can reveal patterns in language use that correlate with different coping strategies, providing empirical evidence to support or refine existing psychological theories. Additionally, machine learning techniques can be employed to create predictive models that assess the likelihood of specific coping strategies based on linguistic features, offering new avenues for research and application.
Overall, interdisciplinary collaboration can lead to the development of more sophisticated tools for emotion analysis, ultimately improving our understanding of how language reflects emotional coping mechanisms and enhancing interventions in fields such as mental health and customer service.