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Mixed-Initiative Real-Time Topic Modeling & Visualization for Crisis Counseling

Published: 18 March 2015 Publication History

Abstract

Text-based counseling and support systems have seen an increasing proliferation in the past decade. We present Fathom, a natural language interface to help crisis counselors on Crisis Text Line, a new 911-like crisis hotline that takes calls via text messaging rather than voice. Text messaging opens up the opportunity for software to read the messages as well as people, and to provide assistance for human counselors who give clients emotional and practical support. Crisis counseling is a tough job that requires dealing with emotionally stressed people in possibly life-critical situations, under time constraints. Fathom is a system that provides topic modeling of calls and graphical visualization of topic distributions, updated in real time. We develop a mixed-initiative paradigm to train coherent topic and word distributions and use them to power real-time visualizations aimed at reducing counselor cognitive overload. We believe Fathom to be the first real-time computational framework to assist in crisis counseling.

References

[1]
Alison Bryant, J., Sanders-Jackson, A., and Smallwood, A. M. Iming, text messaging, and adolescent social networks. Journal of Computer-Mediated Communication 11, 2 (2006), 577--592.
[2]
Blei, D. M. Probabilistic topic models. Communications of the ACM 55, 4 (2012), 77--84.
[3]
Bostock, M. D3. js. Data Driven Documents (2012).
[4]
Chaney, A. J.-B., and Blei, D. M. Visualizing topic models. In ICWSM (2012).
[5]
Christensen, H., Farrer, L., Batterham, P. J., Mackinnon, A., Griffiths, K. M., and Donker, T. The effect of a web-based depression intervention on suicide ideation: secondary outcome from a randomised controlled trial in a helpline. BMJ open 3, 6 (2013).
[6]
Cui, W., Liu, S., Tan, L., Shi, C., Song, Y., Gao, Z., Qu, H., and Tong, X. Textflow: Towards better understanding of evolving topics in text. Visualization and Computer Graphics, IEEE Transactions on 17, 12 (2011), 2412--2421.
[7]
Dinakar, K., Chaney, A. J., Lieberman, H., and Blei, D. M. Real-time topic models for crisis counseling. Twentieth ACM Conference on Knowledge Discovery and Data Mining, Data Science for the Social Good Workshop (2014).
[8]
Dinakar, K., Jones, B., Lieberman, H., Picard, R., Rose, C., Thoman, M., and Reichart, R. You too?! mixed-initiative lda story matching to help teens in distress, 2012.
[9]
Dinakar, K., Weinstein, E., Lieberman, H., and Selman, R. Stacked generalization learning to analyze teenage distress. International AAAI Conference on Weblogs and Social Media (2014).
[10]
Gardner, M. J., Lutes, J., Lund, J., Hansen, J., Walker, D., Ringger, E., and Seppi, K. The topic browser: An interactive tool for browsing topic models. In NIPS Workshop on Challenges of Data Visualization (2010).
[11]
Gianfortoni, P., Adamson, D., and Rosé, C. P. Modeling of stylistic variation in social media with stretchy patterns. In Proceedings of the First Workshop on Algorithms and Resources for Modelling of Dialects and Language Varieties, DIALECTS '11, Association for Computational Linguistics (Stroudsburg, PA, USA, 2011), 49--59.
[12]
Gould, M. S., Cross, W., Pisani, A. R., Munfakh, J. L., and Kleinman, M. Impact of applied suicide intervention skills training on the national suicide prevention lifeline. Suicide and Life-Threatening Behavior 43, 6 (2013), 676--691.
[13]
Gould, M. S., Munfakh, J. L., Kleinman, M., and Lake, A. M. National suicide prevention lifeline: enhancing mental health care for suicidal individuals and other people in crisis. Suicide and Life-Threatening Behavior 42, 1 (2012), 22--35.
[14]
Hedgebeth, D. Data-driven decision making for the enterprise: an overview of business intelligence applications. VINE 37, 4 (2007), 414--420.
[15]
Hoff, L. A., Hallisey, B. J., and Hoff, M. People in crisis: Clinical and diversity perspectives. Taylor & Francis, 2011.
[16]
Hoffman, M., Bach, F. R., and Blei, D. M. Online learning for latent dirichlet allocation. In advances in neural information processing systems (2010), 856--864.
[17]
Horvitz, E. Principles of mixed-initiative user interfaces. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems, ACM (1999), 159--166.
[18]
Kinzel, A., and Nanson, J. Education and debriefing: Strategies for preventing crises in crisis-line volunteers. Crisis: The Journal of Crisis Intervention and Suicide Prevention 21, 3 (2000), 126--134.
[19]
Pallotta, V., Delmonte, R., Vrieling, L., and Walker, D. Interaction mining: the new frontier of call center analytics. Proc. of DART (2011).
[20]
Pratt, M. E. The Future of Volunteers in Crisis Hotline Work. PhD thesis, University of Pittsburgh, 2013.
[21]
Ramage, D., Hall, D., Nallapati, R., and Manning, C. D. Labeled lda: A supervised topic model for credit attribution in multi-labeled corpora. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1-Volume 1, Association for Computational Linguistics (2009), 248--256.
[22]
Rubin, T. N., Chambers, A., Smyth, P., and Steyvers, M. Statistical topic models for multi-label document classification. Machine Learning 88, 1--2 (2012), 157--208.
[23]
Schwartz, R. C., and Rogers, J. R. Suicide assessment and evaluation strategies: A primer for counselling psychologists. Counselling Psychology Quarterly 17, 1 (2004), 89--97.
[24]
Smith, A. 46% of american adults are smartphone owners. Pew Internet & American Life Project (2012).
[25]
Wallach, H. M., Mimno, D. M., and McCallum, A. Rethinking lda: Why priors matter. In NIPS, Y. Bengio, D. Schuurmans, J. D. Lafferty, C. K. I. Williams, and A. Culotta, Eds., Curran Associates, Inc. (2009), 1973--1981.
[26]
Wang, P. S., Lane, M., Olfson, M., Pincus, H. A., Wells, K. B., and Kessler, R. C. Twelve-month use of mental health services in the united states: results from the national comorbidity survey replication. Archives of general psychiatry 62, 6 (2005), 629--640.

Cited By

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  • (2024)Algorithmic SubjectivitiesACM Transactions on Computer-Human Interaction10.1145/366034431:3(1-34)Online publication date: 27-Apr-2024
  • (2024)Real-time assistance in suicide prevention helplines using a deep learning-based recommender system: a randomized controlled trialInternational Journal of Medical Informatics10.1016/j.ijmedinf.2024.105760(105760)Online publication date: Dec-2024
  • (2022)Human-Computer Interaction in Digital Mental HealthInformatics10.3390/informatics90100149:1(14)Online publication date: 22-Feb-2022
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    cover image ACM Conferences
    IUI '15: Proceedings of the 20th International Conference on Intelligent User Interfaces
    March 2015
    480 pages
    ISBN:9781450333061
    DOI:10.1145/2678025
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    Published: 18 March 2015

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    Author Tags

    1. mental health counseling
    2. natural language interfaces
    3. topic modeling
    4. visualizations

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    • Google Faculty Grant
    • Reid Hoffman Fellowship

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    IUI '15 Paper Acceptance Rate 47 of 205 submissions, 23%;
    Overall Acceptance Rate 746 of 2,811 submissions, 27%

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    Cited By

    View all
    • (2024)Algorithmic SubjectivitiesACM Transactions on Computer-Human Interaction10.1145/366034431:3(1-34)Online publication date: 27-Apr-2024
    • (2024)Real-time assistance in suicide prevention helplines using a deep learning-based recommender system: a randomized controlled trialInternational Journal of Medical Informatics10.1016/j.ijmedinf.2024.105760(105760)Online publication date: Dec-2024
    • (2022)Human-Computer Interaction in Digital Mental HealthInformatics10.3390/informatics90100149:1(14)Online publication date: 22-Feb-2022
    • (2022)Detecting changes in help seeker conversations on a suicide prevention helpline during the COVID− 19 pandemic: in-depth analysis using encoder representations from transformersBMC Public Health10.1186/s12889-022-12926-222:1Online publication date: 18-Mar-2022
    • (2021)The Opportunities and Challenges of the First Three Years of Open Up, an Online Text-Based Counselling Service for Youth and Young AdultsInternational Journal of Environmental Research and Public Health10.3390/ijerph18241319418:24(13194)Online publication date: 14-Dec-2021
    • (2021)Analysis and Design of Social Presence in a Computer-Mediated Communication SystemFrontiers in Psychology10.3389/fpsyg.2021.64192712Online publication date: 24-May-2021
    • (2021)Content-Based Recommender Support System for Counselors in a Suicide Prevention Chat Helpline: Design and Evaluation StudyJournal of Medical Internet Research10.2196/2169023:1(e21690)Online publication date: 7-Jan-2021
    • (2021)A Systematic Review on Dyadic Conversation VisualizationsCompanion Publication of the 2021 International Conference on Multimodal Interaction10.1145/3461615.3485396(137-147)Online publication date: 18-Oct-2021
    • (2020)The Effectiveness of Crisis Line Services: A Systematic ReviewFrontiers in Public Health10.3389/fpubh.2019.003997Online publication date: 17-Jan-2020
    • (2020)Engagement With Crisis Text Line Among Subgroups of Users Who Reported SuicidalityPsychiatric Services10.1176/appi.ps.20190014971:4(319-327)Online publication date: 1-Apr-2020
    • Show More Cited By

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