Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology最新文献

Predicting Suicide Risk from Online Postings in Reddit The UGent-IDLab submission to the CLPysch 2019 Shared Task A UGent-IDLab提交给CLPysch 2019共享任务A

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3019

Semere Kiros Bitew, Giannis Bekoulis, Johannes Deleu, Lucas Sterckx, Klim Zaporojets, Thomas Demeester, Chris Develder

引用次数: 6

Towards augmenting crisis counselor training by improving message retrieval 通过改进信息检索来加强危机咨询师的培训

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3001

O. Demasi, Marti A. Hearst, B. Recht

引用次数: 19

Using natural conversations to classify autism with limited data: Age matters 使用自然对话在有限数据下对自闭症进行分类:年龄很重要

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3006

M. Hauser, E. Sariyanidi, B. Tunç, C. Zampella, E. Brodkin, R. Schultz, J. Parish-Morris

{"title":"Using natural conversations to classify autism with limited data: Age matters","authors":"M. Hauser, E. Sariyanidi, B. Tunç, C. Zampella, E. Brodkin, R. Schultz, J. Parish-Morris","doi":"10.18653/v1/W19-3006","DOIUrl":"https://doi.org/10.18653/v1/W19-3006","url":null,"abstract":"Spoken language ability is highly heterogeneous in Autism Spectrum Disorder (ASD), which complicates efforts to identify linguistic markers for use in diagnostic classification, clinical characterization, and for research and clinical outcome measurement. Machine learning techniques that harness the power of multivariate statistics and non-linear data analysis hold promise for modeling this heterogeneity, but many models require enormous datasets, which are unavailable for most psychiatric conditions (including ASD). In lieu of such datasets, good models can still be built by leveraging domain knowledge. In this study, we compare two machine learning approaches: the first approach incorporates prior knowledge about language variation across middle childhood, adolescence, and adulthood to classify 6-minute naturalistic conversation samples from 140 age- and IQ-matched participants (81 with ASD), while the other approach treats all ages the same. We found that individual age-informed models were significantly more accurate than a single model tasked with building a common algorithm across age groups. Furthermore, predictive linguistic features differed significantly by age group, confirming the importance of considering age-related changes in language use when classifying ASD. Our results suggest that limitations imposed by heterogeneity inherent to ASD and from developmental change with age can be (at least partially) overcome using domain knowledge, such as understanding spoken language development from childhood through adulthood.","PeriodicalId":201097,"journal":{"name":"Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116906843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Suicide Risk Assessment on Social Media: USI-UPF at the CLPsych 2019 Shared Task 社交媒体上的自杀风险评估:USI-UPF在CLPsych 2019共享任务上

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3021

E. A. Ríssola, Diana Ramírez-Cifuentes, Ana Freire, F. Crestani

引用次数: 4

Linguistic Analysis of Schizophrenia in Reddit Posts Reddit帖子中精神分裂症的语言分析

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3009

Jonathan Zomick, Sarah Ita Levitan, M. Serper

引用次数: 26

Depressed Individuals Use Negative Self-Focused Language When Recalling Recent Interactions with Close Romantic Partners but Not Family or Friends 抑郁的人在回忆最近与亲密恋人的互动时，会使用消极的自我关注语言，而不是家人或朋友

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3008

Taleen Nalabandian, Molly Ireland

引用次数: 10

CLaC at CLPsych 2019: Fusion of Neural Features and Predicted Class Probabilities for Suicide Risk Assessment Based on Online Posts 基于网络帖子的自杀风险评估的神经特征融合和预测类别概率

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3004

Elham Mohammadi, Hessam Amini, Leila Kosseim

引用次数: 21

ConvSent at CLPsych 2019 Task A: Using Post-level Sentiment Features for Suicide Risk Prediction on Reddit 在Reddit上使用后级情感特征进行自杀风险预测

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3024

Kristen Allen, Shrey Bagroy, Alexander L Davis, T. Krishnamurti

引用次数: 10

The importance of sharing patient-generated clinical speech and language data 共享患者生成的临床语音和语言数据的重要性

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 2019-06-01 DOI: 10.18653/v1/W19-3007

Kathleen C. Fraser, N. Linz, Hali Lindsay, A. König

引用次数: 5

Suicide Risk Assessment with Multi-level Dual-Context Language and BERT 基于多层次双语境语言和BERT的自杀风险评估

Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology Pub Date : 1900-01-01 DOI: 10.18653/v1/W19-3005

Matthew Matero, Akash Idnani, Youngseo Son, Salvatore Giorgi, Huy-Hien Vu, Mohammadzaman Zamani, Parth Limbachiya, Sharath Chandra Guntuku, H. A. Schwartz

{"title":"Suicide Risk Assessment with Multi-level Dual-Context Language and BERT","authors":"Matthew Matero, Akash Idnani, Youngseo Son, Salvatore Giorgi, Huy-Hien Vu, Mohammadzaman Zamani, Parth Limbachiya, Sharath Chandra Guntuku, H. A. Schwartz","doi":"10.18653/v1/W19-3005","DOIUrl":"https://doi.org/10.18653/v1/W19-3005","url":null,"abstract":"Mental health predictive systems typically model language as if from a single context (e.g. Twitter posts, status updates, or forum posts) and often limited to a single level of analysis (e.g. either the message-level or user-level). Here, we bring these pieces together to explore the use of open-vocabulary (BERT embeddings, topics) and theoretical features (emotional expression lexica, personality) for the task of suicide risk assessment on support forums (the CLPsych-2019 Shared Task). We used dual context based approaches (modeling content from suicide forums separate from other content), built over both traditional ML models as well as a novel dual RNN architecture with user-factor adaptation. We find that while affect from the suicide context distinguishes with no-risk from those with “any-risk”, personality factors from the non-suicide contexts provide distinction of the levels of risk: low, medium, and high risk. Within the shared task, our dual-context approach (listed as SBU-HLAB in the official results) achieved state-of-the-art performance predicting suicide risk using a combination of suicide-context and non-suicide posts (Task B), achieving an F1 score of 0.50 over hidden test set labels.","PeriodicalId":201097,"journal":{"name":"Proceedings of the Sixth Workshop on Computational Linguistics and Clinical Psychology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121825743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 87