Table 3 Exploring the predictive relationship between social media usage and depression.

Hartanto et al.¹⁵¹

Social media usage increases among depressive individuals

Figueredo et al.⁷⁸

Semantic mapping of emoticons improves the performance.

Stankevich et al.⁷⁹

Future work needs to involve applying semantic role labeling to obtain better results.

Lara et al.⁷⁷

DeepBoSE outperforms conventional Bag-of-Features(BoF) representations.

Hussain et al.¹⁵²

Proposed depression lexicons that distinguish depressive individuals.

Ramiandrisoa et al.⁸⁶

Analyzing users’ social signals could be considered for further analysis.

Liaw et al.¹⁵³

Topic modeling features such as liked tweets can be useful.

Guo et al.⁸⁴

Fused the lexical features using a correlation-based metric to enhance prediction effectiveness.

Cui et al.⁸³

Capture deep emotional information from the input embeddings with a pre-trained TextCNN.

Zogan et al.⁸⁷

The model captures semantic features from user timelines for depression detection.

Tlatelpa et al.⁸⁰

User characteristics and sentiment analysis improved depression detection performance.

Cha et al.⁸²

Proposed lexicon features for depression detection.

Primack et al.¹⁵⁴

Using multiple social media platforms is associated with depression.

Primack et al.¹⁵⁵

Social media use is associated with the development of depression.

Vedula et al.¹⁵⁶

Depressed users exhibit reduced online activities, increased negative sentiment, and self-focused pronoun usage.

Nesi et al.¹⁵⁷

More frequent negative emotional reactions to social media are linked to more severe depression symptoms, especially among female subjects.

Thorisdottir et al.¹⁵⁸

Time spent on social media has a stronger relationship with emotional distress among female subjects.

Ghosh et al.¹⁵⁹

Depressed users frequently use negative words and mostly post late at night, in addition to increased use of personal pronouns and sharing personal events.

Aragon et al.¹⁶⁰

Representations based on fine-grained emotions can more comprehensively capture users experiencing depression.

Puukko et al.¹⁶¹

Depressed individuals increasingly use active social media during early and late adolescence.

Robinson et al.¹⁶²

Depressed individuals are more likely to compare themselves to others and dislike being tagged in self-perceived unflattering pictures.

Choudhury et al.¹⁶³

Social media can provide valuable indicators of depression onset, including decreased social activities, increased negative emotions, focus on personal and medical issues, and more frequent expressions of religious involvement.