2026-09-18T21:22:03Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/913062026-06-06T00:49:28Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Henry A. Lieberman.
Chen, Ge (Ge Jackie)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2014-11-04T20:28:55Z
2014-11-04T20:28:55Z
2014
2014
http://hdl.handle.net/1721.1/91306
893856032
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
21
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 53-54).
Crisis Text Line supports people with mental health issues through texting. Unfortunately, support is limited by the number of counselors and the time each counselor has for clients, as well as the cognitive load on counselors from managing multiple conversations simultaneously. We conducted a contextual inquiry with crisis counselors to find contributing problems in their work flow. We believe topic modeling can provide automatic summaries of conversation text to augment note-taking and transcript-reading. Four simple and familiar visualizations were developed to present the model data: 1) a list of conversation topics, 2) a donut chart of topic percentages, 3) a line chart of topic trends, and 4) a scatter plot of specific topic points in the text. Our hypothesis is that these visualizations will help counselors spend more time on clients without overloading the counselors. The visualizations were evaluated through a user study to determine their effectiveness against a control interface.
by Ge (Jackie) Chen.
M.Eng.
54 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Visualizations for mental health topic models
Thesis
application/pdf
Publication
unknown
unknown
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<Abstract>Crisis Text Line supports people with mental health issues through texting. Unfortunately, support is limited by the number of counselors and the time each counselor has for clients, as well as the cognitive load on counselors from managing multiple conversations simultaneously. We conducted a contextual inquiry with crisis counselors to find contributing problems in their work flow. We believe topic modeling can provide automatic summaries of conversation text to augment note-taking and transcript-reading. Four simple and familiar visualizations were developed to present the model data: 1) a list of conversation topics, 2) a donut chart of topic percentages, 3) a line chart of topic trends, and 4) a scatter plot of specific topic points in the text. Our hypothesis is that these visualizations will help counselors spend more time on clients without overloading the counselors. The visualizations were evaluated through a user study to determine their effectiveness against a control interface.</Abstract>
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