  Due to the worldwide accessibility to the Internet along with the continuous
advances in mobile technologies, physical and digital worlds have become
completely blended, and the proliferation of social media platforms has taken a
leading role over this evolution. In this paper, we undertake a thorough
analysis towards better visualising and understanding the factors that
characterise and differentiate social media users affected by mental disorders.
We perform different experiments studying multiple dimensions of language,
including vocabulary uniqueness, word usage, linguistic style, psychometric
attributes, emotions' co-occurrence patterns, and online behavioural traits,
including social engagement and posting trends. Our findings reveal significant
differences on the use of function words, such as adverbs and verb tense, and
topic-specific vocabulary, such as biological processes. As for emotional
expression, we observe that affected users tend to share emotions more
regularly than control individuals on average. Overall, the monthly posting
variance of the affected groups is higher than the control groups. Moreover, we
found evidence suggesting that language use on micro-blogging platforms is less
distinguishable for users who have a mental disorder than other less
restrictive platforms. In particular, we observe on Twitter less quantifiable
differences between affected and control groups compared to Reddit.
