Available Online: 29 June 2020
Lumontod, Robinson Z., III*
Central Luzon State University, Philippines (email@example.com)
Depression remains one of the leading problems around the world. Partly, the problem stems from the fact that depression is still difficult to diagnose using traditional assessment tools. A few pieces of evidence suggest that text analysis is capable of identifying psychological states and mental issues including depression. However, this method has not been tested in the Philippines. The main purpose of this study, therefore, was to determine clues of depression and suicidal ideation in college students’ writing using the online version of LIWC, a computerized text analysis. The present study was conducted at Central Luzon State University, Philippines where 159 undergraduate students participated. Using correlational analysis, several important findings were found. First, college students with a high level of depression and suicidal ideation tend to write more personal pronouns such as “I”, “me”, and “my” in their writing. Second, LIWC traditional dimensions such as I-words and negative emotions show a significant link with depression but only the I-words dimension was significantly associated with suicidal ideation. Third, LIWC summary variables such as clout and emotional tone also show a significant relationship with depression and suicidal ideation. Furthermore, regression analysis suggests that these LIWC domains were significant predictors of depression. However, only emotional tone was found to have a modest but significant influence on suicidal ideation. Lastly, the length of the essay was significantly correlated with depression but not with suicidal ideation. The theoretical and practical implications of the findings are discussed.
Keywords: depression; suicidal ideation; LIWC; text analysis; college students
Cite this article:
Lumontod, R. Z., III. (2020). Seeing the invisible: Extracting signs of depression and suicidal ideation from college students’ writing using LIWC a computerized text analysis. International Journal of Research Studies in Education, 9(4), 31-44. https://doi.org/10.5861/ijrse.2020.5007