Linguistic Markers of Cognitive Decline in Multiple Sclerosis

Jayita Iyengar

Keywords: Multiple Sclerosis, Cognitive Decline, Natural Language Processing, Social Media Analysis, Linguistic Features, Biomarkers

TL;DR: Subtle cognitive decline in Multiple Sclerosis can be detected early by analyzing changes in patients’ language on social media, revealing measurable shifts in meaning, structure, and emotional expression over time.

Abstract: While cognitive changes due to Multiple Sclerosis are typically very subtle and include decreased processing speed, memory challenges, and difficulties with communication, they can begin to appear before diagnosis. This research applies natural language processing to analyze communication patterns and monitor cognitive changes over time. A public, anonymized Reddit dataset from the r/MultipleSclerosis community was used to compare language use between “patient” and “caregiver” users. Transformer-based computational models assessed aspects of language, including semantic density, coherence, vocabulary use, and emotional expression. While caregiver language remained stable over time, patient language demonstrated quantifiable declines in meaning and structure (semantic density -13.11%, linguistic entropy -2.58%) and increased emotional variability (emotional neutrality -17.1%). These results indicate that text-based analysis can detect minute shifts in communication. Findings from cell-based studies utilizing the GEO astrocyte datasets examined whether biomarkers associated with cognitive decline differed in populations at risk (GFAP ↑ p<0.01, SNAP25 ↑ p<0.05, NEFL ↓ p<0.05). This study presents a unique tool for identifying cognitive changes through text-based analysis, demonstrating that social media discourse can offer insight into cognitive abilities as a novel lens for understanding Multiple Sclerosis progression.

Email Sharing: We authorize the sharing of all author emails with Program Chairs.

Data Release: We authorize the release of our submission and author names to the public in the event of acceptance.

Submission Number: 7