Narrative trajectory data from Strava have the capacity to improve our understanding of runners’ experiences and environmental perceptions. Despite technological advancements in GIS and computational linguistics to better analyze spatial narratives, qualitative facets of social fitness data remain seldom researched. User narratives, or posts, on social fitness apps have the potential to enhance planning for active and equitable communities. Strava, a popular fitness social media app for runners, consists of users who share text narratives and images linked to spatial trajectories. This study explored spatiotemporal and gendered patterns of sentiment associated with Strava narratives in Metropolitan Vancouver between 2011 and 2021. A open authorization-based portal collected activity trajectories and descriptions from 146 runners. Valence Aware Dictionary and sEntiment Reasoner (VADER) sentiment analysis was conducted on 91,764 activity narratives to measure the degree of overall feelings during runs along a spectrum from negative to positive (-1 to +1). Then, a thematic analysis of polarized posts (sentiment extremes) uncovered seven main themes: (1) interpersonal interaction, (2) psychological aspects, (3) weather and atmospheric conditions, (4) bodily experience, (5) surroundings, (6) path, and (7) supportive equipment. Findings uncover the influence of gender on the accessibility of running environments and provide insight into diverse runner experiences. This study explores novel GIS approaches for extracting meaning from qualitative social fitness data and offers guidance for spatial mixed methods analyses in related fields.