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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2021
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2106.12976 |
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| _version_ | 1866908467667664896 |
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| author | Lahnala, Allison Zhao, Yuntian Welch, Charles Kummerfeld, Jonathan K. An, Lawrence Resnicow, Kenneth Mihalcea, Rada Pérez-Rosas, Verónica |
| author_facet | Lahnala, Allison Zhao, Yuntian Welch, Charles Kummerfeld, Jonathan K. An, Lawrence Resnicow, Kenneth Mihalcea, Rada Pérez-Rosas, Verónica |
| contents | A growing number of people engage in online health forums, making it important to understand the quality of the advice they receive. In this paper, we explore the role of expertise in responses provided to help-seeking posts regarding mental health. We study the differences between (1) interactions with peers; and (2) interactions with self-identified mental health professionals. First, we show that a classifier can distinguish between these two groups, indicating that their language use does in fact differ. To understand this difference, we perform several analyses addressing engagement aspects, including whether their comments engage the support-seeker further as well as linguistic aspects, such as dominant language and linguistic style matching. Our work contributes toward the developing efforts of understanding how health experts engage with health information- and support-seekers in social networks. More broadly, it is a step toward a deeper understanding of the styles of interactions that cultivate supportive engagement in online communities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2106_12976 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Exploring Self-Identified Counseling Expertise in Online Support Forums Lahnala, Allison Zhao, Yuntian Welch, Charles Kummerfeld, Jonathan K. An, Lawrence Resnicow, Kenneth Mihalcea, Rada Pérez-Rosas, Verónica Computation and Language A growing number of people engage in online health forums, making it important to understand the quality of the advice they receive. In this paper, we explore the role of expertise in responses provided to help-seeking posts regarding mental health. We study the differences between (1) interactions with peers; and (2) interactions with self-identified mental health professionals. First, we show that a classifier can distinguish between these two groups, indicating that their language use does in fact differ. To understand this difference, we perform several analyses addressing engagement aspects, including whether their comments engage the support-seeker further as well as linguistic aspects, such as dominant language and linguistic style matching. Our work contributes toward the developing efforts of understanding how health experts engage with health information- and support-seekers in social networks. More broadly, it is a step toward a deeper understanding of the styles of interactions that cultivate supportive engagement in online communities. |
| title | Exploring Self-Identified Counseling Expertise in Online Support Forums |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2106.12976 |