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Technology and Dementia Preconference.

Shira Darchi1, Yuval Pinter2, Talya Sadeh2

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Summary
This summary is machine-generated.

Analyzing social media language can detect cognitive decline. Alzheimer's Disease (AD) patients use fewer internal details and more past tense/emotional words than controls, indicating potential for early dementia detection.

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Area of Science:

  • Computational linguistics
  • Neuroscience
  • Digital psychiatry

Background:

  • Natural Language Processing (NLP) shows promise for identifying linguistic markers of Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD).
  • Previous studies, often using curated texts, achieved 80%-85% classification accuracy.
  • Social media offers ecologically valid, continuous assessment of linguistic changes for cognitive decline detection.

Purpose of the Study:

  • To explore the potential of detecting cognitive decline through online activity on Reddit.
  • To contribute to developing a complex model for early detection of cognitive deterioration from online behavior.
  • To analyze linguistic and behavioral markers in social media data for dementia detection.

Main Methods:

  • Employed a Self-Disclosure approach to identify self-reported AD cases on Reddit.
  • Collected and analyzed data from 42 Reddit users (20 with AD, 22 matched controls).
  • Examined online engagement patterns and linguistic shifts using DistilBERT for automatic scoring of internal and external details.

Main Results:

  • A significant group effect was found on word usage (p < .001).
  • AD patients used significantly fewer internal/episodic words compared to controls (p < .001).
  • AD patients showed increased use of past tense, emotional, function, and social words, while controls used more analytic language.

Conclusions:

  • Significant differences in online activity and language patterns exist between AD patients and controls.
  • Analysis of social media activity provides valuable insights into cognitive decline.
  • Future models leveraging these markers may enable scalable, non-invasive early dementia detection.