Defining patients with depressive disorder by using textual information

Tetsuaki Nakamura*, Kay Kubo, Yasuyuki Usuda, Eiji Aramaki

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Depression has been one of the serious social problems of the modern society, due to the prolonged economic stagnation, the increasing number of unemployment rate, and so on. Diseases that require long-term treatments, such as cancer and chronic diseases, are also the major cause of depression, and, eventually, that often leads the patients to committing suicide. Such circumstance requires some urgent means to prevent depression, especially of those who are suffering diseases. In this study, to propose one of the tools for preventing depression or to detect depression at its early stage of suffering, we analyze 200 blog articles to set-up an "evaluation index" that is capable of measuring the tendency of depression from written texts of the long-term patients. Firstly, we collect and analyze blog articles written by the patients who are suffering depression, as well as the articles written by those who are not suffering depression as a comparison. From the analysis, we propose an index for depression measurement. With this index, secondly, we make an analysis on the articles that are posted on a special SNS, which is particularly available for long-term patients. It comes out that posting articles on SNS for more than 12 months may mitigate depression (or depressive symptoms). This outcome suggests the possibility of SNS posting against depression for the long-term patients.

Original languageEnglish
Title of host publicationBig Data Becomes Personal
Subtitle of host publicationKnowledge into Meaning - Papers from the AAAI Spring Symposium, Technical Report
PublisherAI Access Foundation
Pages39-44
Number of pages6
ISBN (Print)9781577356547
Publication statusPublished - 2014
Externally publishedYes
Event2014 AAAI Spring Symposium - Palo Alto, CA, United States
Duration: 2014 Mar 242014 Mar 26

Publication series

NameAAAI Spring Symposium - Technical Report
VolumeSS-14-01

Conference

Conference2014 AAAI Spring Symposium
Country/TerritoryUnited States
CityPalo Alto, CA
Period14/3/2414/3/26

ASJC Scopus subject areas

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Defining patients with depressive disorder by using textual information'. Together they form a unique fingerprint.

Cite this