Observer Effect in Social Media Use
Koustuv Saha, Pranshu Gupta, Gloria Mark, Emre Kiciman, Munmun De Choudhury
摘要
Research has revealed the potential of social media as a source of large-scale, verbal, and naturalistic data for human behavior both in real-time and longitudinally. However, the in-practice utility of social media to assess and support wellbeing will only be realized when we account for extraneous factors. One such factor that might confound our ability to make inferences is the phenomenon of the "observer effect"-that individuals may deviate from their otherwise typical social media use because of the awareness of being monitored. This paper conducts a causal study to measure the observer effect in longitudinal social media use. We operationalized the observer effect in two dimensions of social media (Facebook) use-behavioral and linguistic changes. Participants consented to Facebook data collection over an average retrospective period of 82 months and an average prospective period of 5 months around the enrollment date to our study. We measured how they deviated from their expected social media use after enrollment. We obtained expected use by extrapolating from historical use using time-series (ARIMA) forecasting. We find that the deviation in social media use varies across individuals based on their psychological traits. Individuals with high cognitive ability and low neuroticism immediately decreased posting after enrollment, and those with high openness significantly increased posting. Linguistically, most individuals decreased the use of first-person pronouns, reflecting lowered sharing of intimate and self-attentional content. While some increased posting about public-facing events, others increased posting about family and social gatherings. We validate the observed changes with respect to psychological traits drawing from psychology and behavioral science theories, such as self-monitoring, public self-consciousness, and self-presentation. The findings provide recommendations to correct observer effects in social media data-driven assessments of human behavior.
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