Activities on Facebook Reveal the Depressive State of Users

Abstract

BackgroundAs online social media have become prominent, much effort has been spent on identifying users with depressive symptoms in order to aim at early diagnosis, treatment, and even prevention by using various online social media. In this paper, we focused on Facebook to discern any correlations between the platform’s features and users’ depressive symptoms. This work may be helpful in trying to reach and detect large numbers of depressed individuals more easily.ObjectiveOur goal was to develop a Web application and identify depressive symptom–related features from users of Facebook, a popular social networking platform.Methods55 Facebook users (male=40, female=15, mean age 24.43, SD 3.90) were recruited through advertisement fliers distributed to students in a large university in Korea. Using EmotionDiary, the Facebook application we developed, we evaluated depressive symptoms using the Center for Epidemiological Studies-Depression (CES-D) scale. We also provided tips and facts about depression to participants and measured their responses using EmotionDiary. To identify the Facebook features related to depression, correlation analyses were performed between CES-D and participants’ responses to tips and facts or Facebook social features. Last, we interviewed depressed participants (CES-D≥25) to assess their depressive symptoms by a psychiatrist.ResultsFacebook activities had predictive power in distinguishing depressed and nondepressed individuals. Participants’ response to tips and facts, which can be explained by the number of app tips viewed and app points, had a positive correlation (P=.04 for both cases), whereas the number of friends and location tags had a negative correlation with the CES-D scale (P=.08 and P=.045 respectively). Furthermore, in finding group differences in Facebook social activities, app tips viewed and app points resulted in significant differences (P=.01 and P=.03 respectively) between probably depressed and nondepressed individuals.ConclusionsOur results using EmotionDiary demonstrated that the more depressed one is, the more one will read tips and facts about depression. We also confirmed depressed individuals had significantly fewer interactions with others (eg, decreased number of friends and location tagging). Our app, EmotionDiary, can successfully evaluate depressive symptoms as well as provide useful tips and facts to users. These results open the door for examining Facebook activities to identify depressed individuals. We aim to conduct the experiment in multiple cultures as well.

The Relationship Between Online Social Networking and Depression: A Systematic Review of Quantitative Studies

“…The total number of participants across all reviewed studies was 35,044. Research was identified from 14 countries including the Philippines, 20,21 Turkey, 22,23 Serbia, 24,25 Australia, 26 Greece, 27 and Korea, 28 reflecting the global nature of the phenomenon under study. Participant age ONLINE SOCIAL NETWORKING AND DEPRESSION !…”

Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality

“…They used crowdsourcing to screen Twitter users with the CES-D test (Beekman et al, 1997), while others analyzed one year of Facebook status updates for DSM diagnostic critera of a Major Depressive Episode (Moreno et al, 2011). In addition, Park et al (2013) predicted results of the Beck Depression Inventory (Beck et al, 1961).…”

“…In fact, even Internet usage itself seems to vary as a function of being depressed (Katikalapudi et al, 2012). Other behaviors include social networking (Moreno et al, 2011) and differences in location sharing on Facebook (Park et al, 2013).…”

Correlations between objective behavioral features collected from mobile and wearable devices, and depressive mood symptoms in affective disorders: A systematic review (Preprint)

“…Simple mood scales for self-assessment such as a 7-point selection from -3 till 3 have shown statistically significant correlations with clinical validated rating scales such as the HDRS [57]. For example, there is high correlation between the commonly used assessments methods of depression; PHQ-9, BDI, and the HDRS (lowest PHQ-9 vs HDRS: r = .728) [72 Table 3], and CES-D and BDI have also been shown to be highly correlated (r = .839, p < .01) [73]. Patient-based outcome measures such as PHQ-9 and BDI have the benefit of being conducted outside the clinic, target very specific symptoms, exclude clinician bias, and facilitate the doctor-patient communication, while it has some drawbacks such as a biased response depending on the recipient, and a lack of meaningful interpretation of the changes to the outcome value [74].…”