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Vulnerability Dictionary: Language Use During Times of Crisis and Uncertainty

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Social, Cultural, and Behavioral Modeling (SBP-BRiMS 2023)

Abstract

Studying the expression of vulnerability – the psychological state that arises in moments of uncertainty, risk, and emotional exposure – is key to understanding how individuals cope during time of crisis. In this study, we synthesize past theoretical and qualitative work on vulnerability and present a psycholinguistic dictionary featuring seven different lexicons commonly associated with vulnerability language: accusation, incompetence, lack of trust, riot, out-group speech, agency, and helplessness. To validate our dictionary, we apply the identified lexicons to three different datasets and then generate samples for evaluation by two independent human labelers. The comparison between the human-labeled and machine-generated results demonstrates the dictionary’s robustness, achieving a Cohen’s Kappa of 0.66 in inter-rater reliability among two labelers and an overall accuracy of 0.74 when treating human label as the ground truth. With the dictionary, we aim to provide a nuanced understanding and detection of vulnerability language on social media content and provide a foundation for text feature extraction for traditional machine learning methods.

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Acknowledgements

This work was supported in part by ONR MURI Persuasion, Identity & Morality in Social-Cyber Environments award # N00014-21-12749 through a grant and the Center for Computational Analysis of Social and Organization Systems (CASOS). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing official policies, either expressed or implied, of ONR Office or the U.S. government.

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Correspondence to Wenjia Hu .

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Hu, W., Jin, Z., Carley, K.M. (2023). Vulnerability Dictionary: Language Use During Times of Crisis and Uncertainty. In: Thomson, R., Al-khateeb, S., Burger, A., Park, P., A. Pyke, A. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2023. Lecture Notes in Computer Science, vol 14161. Springer, Cham. https://doi.org/10.1007/978-3-031-43129-6_11

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  • DOI: https://doi.org/10.1007/978-3-031-43129-6_11

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