Users’ Motivations for Facebook Unfriending During the COVID-19 Pandemic: Survey Study

Abstract

Background Social networking sites (SNSs) such as Facebook have been central to the global exchange of health-related information throughout the COVID-19 pandemic, but during this time, increased web-based interactions proved to be a source of stress and conflict for many SNS users. Prior research suggests that many users have engaged in significant boundary regulation during this period, using behaviors such as unfriending to refine and reorient their social networks in response to pandemic-related information. Objective This study aimed to examine Facebook unfriending during and in relation to the first year of the pandemic to better understand how SNS users have managed and maintained their social networks around the COVID-19 pandemic. On the one hand, unfriending may be motivated by an attempt to protect the utility and accuracy of a user’s informational environment. On the other hand, it may be motivated by a desire to tune out alternative viewpoints and opinions. Both motivations may have significant implications for public health discourse and outcomes. Methods A sample of 824 active Facebook users (drawn from a representative survey of 1000 American adults) was analyzed using a series of logit regression models. Survey respondents were selected using a stratified quota sampling approach to ensure a representative sample of the US population. Balanced quotas were determined (by the region of the country) for sex, age, race, ethnicity, and political affiliation. Results In total, 31.7% (261/824) of active Facebook users unfriended at least one account over COVID-19 pandemic–related posts during the first year of the pandemic. The most common reasons for unfriending included “making political comments about COVID-19” (191/824, 23.2%) and “posting information that was inconsistent with public health guidelines” (162/824, 19.7%). As hypothesized, reliance on Facebook for COVID-19 pandemic–related news and information was associated with a greater likelihood of unfriending, particularly in response to information that was inconsistent with public health guidelines. Political factors (particularly partisan intensity) were also predictive of unfriending, especially in the case of COVID-19 pandemic–related disagreements. Conclusions Both information utility concerns and political factors were associated with a greater likelihood of COVID-19 pandemic–related unfriending, although the magnitude of the effects associated with utility appears to be greater. Although utility-motivated unfriending may lead to more reliable health information experiences for some SNS users, the tendency of consumers to assess accuracy and credibility on the basis of partisan predilections obscures this finding and warrants further consideration.

Social Media Authentication and Users’ Assessments of Health Information: Random Assignment Survey Experiment

“…This hypothesis was supported by the findings, and for both scenarios, the marginal probability that respondents interpreted the post as accurate went up notably as their reliance on social media for health information increased ( Figure 1 ). Several recent studies have shown that SNS users who view their social networks as a source of news and information place a greater premium on information utility than others [ 38 - 40 ]. Platform literacy may also be a factor in this relationship, as those who rely on and use SNS sites more heavily are likely to become better adept at adjudicating the quality of information on those platforms.…”

“…Finally, we hypothesize a positive correlation between reliance on social media for health information and positive assessments of information accuracy. Recent evidence suggests that SNS users who rely more heavily on social platforms for news and information place a greater premium on utility when managing their information exposure [ 38 - 40 ]. Moreover, to the extent that reliance corresponds with greater frequency of use , it can be inferred that platform literacy will increase, leading to more accurate assessments of information quality, regardless of visual heuristics.…”