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Global Translational Medicine Sleep and emotion rhythmicity in tweets

text-mining algorithms could be applied benevolently method. Large-scale studies are required to assess the
to identify individuals susceptible to emotional distress stability of intra-individual interactions between dRARs
from circadian and sleep-related disruption, which could and emotional tweet content across a larger and diverse
facilitate the administration of “Just-In-Time Adaptive population.
Interventions,” or signpost to appropriate support. One From a translational perspective, future studies may
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of the reasons that existing suicide prevention approaches consider assessment of clinical validity among known
have had limited impact on suicide rates is that prevention “at-risk” populations as all the lexicons used in NLP
interventions are too slow for the dynamic temporal methods such as sentiment analysis and LIWC are based on
nature of suicide ideation, which fluctuates in real- healthy individuals. Once the goal of these methodologies
time. In particular, during the night, when suicide risk becomes the identification of clinically salient emotional
is substantially elevated and support mechanisms are distress, one must consider the extent to which we
scare, social media monitoring could provide timely and can consider these normative datasets to be valid. We
ecological support in the form of counseling, or referral recommend the development of lexicons based on distinct
to 24-h telehealth services when it is most needed. These clinical populations (e.g., major depressive disorder,
interventions may complement or even integrate with generalized anxiety disorder), which may maximize the
automated harm-prevention mechanisms present on sensitivity of these models. Moreover, language by nature
social media sites, such as “pop-ups” offering support differs drastically among cultures, and societies. Therefore,
resources whenever a user’s activity is flagged due to the it is important to consider whether models trained using
use of keywords associated with suicide. Nevertheless, one particular language be transferred to another, as well
the implementation of these methods presents a number as whether these models perform equally well across
of methodological and legal challenges, which we discuss different populations. Equally important is the question of
over the proceeding sections.
how differences in language are perceived across different
3. Methodological challenges genders, ethnic identities, races, and cultures, and how
their relationship with the 24-h cycle should be considered.
3.1. Determining validation and alignment with Given that certain cultures, ethnicities, and genders
circadian rhythms communicate emotion much more readily than others, it

Much in the same manner that wearable devices which is critical to consider how conspicuous language should be
track sleep must be compared against gold-standard before it is considered to be indicative of emotional distress.
metrics of sleep, examinations of how sleep estimates from Nevertheless, obtaining this demographic information
dRARs align with predetermined benchmarks for accuracy from social media may prove unreliable, due to the limited
must be conducted, by assessing their synchronicity with nature of the source data (a user’s profile). Much in the
well-defined biological (e.g., circadian), environmental same way that disorder-specific models may contribute
(e.g., night/day or light/dark) or social rest-activity (e.g., toward increased precision for the detection of emotional
work-leisure) rhythms when measured using techniques distress, models which adapt to the differences in sleep
commonly held as accurate assays of these rhythms. For behaviors (e.g., chronotype, bi-phasic sleeping or siesta
instance, determination of the peak of dRARs activity cultures) may prove beneficial. However, consideration
relative to one’s dim light melatonin onset peak could of how to considerately integrate these data with other
provide a window into alignment with endogenous sources of demographic meta-data must first be addressed.
biological rhythms. Most relevant are comparisons with
24-h waist-actigraphy (a gold-standard for rest-activity 3.2. Defining sleep window with minimal datapoints
rhythms [RAR] assessments), which would represent a Perhaps the most salient methodological challenge
logical next-step in this validation pipeline and necessitate associated with deriving RARs from social media use is
comparison of how accurately measurements of L5 and the continuity and completeness of the data. Thorough
M10 (most active 10/24 h) align between dRARs and sensitivity analyses to determine both the minimum
movement RARs. Such validation studies should employ amount of data are required to accurately determine
standardized approaches and recommended guidelines rhythms, as well as the precision points at which further
(for further details see Smith et al. [2018] ) for traditional data brings no further gain in model accuracy. These
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RAR assessment in performing these comparisons. parameters should be determined to ensure the credibility
Crucially, as we demonstrated this approach on a single of predictions, as well as protection against unnecessary
user, generalizability of these findings is limited, and exposure of data when it is not necessary to inform models.
should only be considered as a proof-of-concept of the Although the present study focused exclusively on social

Volume 4 Issue 2 (2025) 54 doi: 10.36922/gtm.5176