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Department of Informatics

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The Department of Informatics at UC Irvine is at the forefront of exploring the exciting challenges that arise from the intersection of people, information and technology. The department brings together scholars, students and practitioners to improve our understanding of technology’s extraordinary impact and to create innovations that redefine how we experience the world.

Department of Informatics

There are 234 publications in this collection, published between 1972 and 2021.
Open Access Policy Deposits (234)

4. All together now: Synchronization, speed, and the failure of narrativity

This paper looks at interconnections between social, scientific, and technical time over the period since the Enlightenment. The underlying argument is that each of these can be woven into a single narrative of our experience and description of time over that period. In particular, I maintain that the synchronization of social and natural time into ever smaller, interchangeable units has culminated today in the evacuation of the narrative of progress in favor of an ideology of the eternal present. Contra technologically determinist characterizations that claim a fundamental historical disjuncture occurring with the development of computers, I claim that this timeless present has historical roots going back to the origin of industrial societies through the age of Victorian certainty to our current epoch. The multiple times described here are argued to be telling a single story. I demonstrate this through developing a historiographical principle of infrastructural inversion, which foregrounds a common set of "techniques dispositifs" operating in the apparently separate worlds of science and industry. The assertion here is that our experiences and perceptions of time are deeply imbricated in our information infrastructures. I further argue that these ideological charged times are not hegemonic; they merely describe a motivating managerial vision of a proximate future.

Why do people oppose mask wearing? A comprehensive analysis of US tweets during the COVID-19 pandemic.

Objective

Facial masks are an essential personal protective measure to fight the COVID-19 pandemic. However, the mask adoption rate in the US is still less than optimal. This study aims to understand the beliefs held by individuals who oppose the use of facial masks, and the evidence that they use to support these beliefs, to inform the development of targeted public health communication strategies.

Materials and methods

We analyzed a total of 771,268 US-based tweets between January to October 2020. We developed machine-learning classifiers to identify and categorize relevant tweets, followed by a qualitative content analysis of a subset of the tweets to understand the rationale of those opposed mask wearing.

Results

We identified 267,152 tweets that contained personal opinions about wearing facial masks to prevent the spread of COVID-19. While the majority of the tweets supported mask wearing, the proportion of anti-mask tweets stayed constant at about 10% level throughout the study period. Common reasons for opposition included physical discomfort and negative effects, lack of effectiveness, and being unnecessary or inappropriate for certain people or under certain circumstances. The opposing tweets were significantly less likely to cite external sources of information such as public health agencies' websites to support the arguments.

Discussion and conclusion

Combining machine learning and qualitative content analysis is an effective strategy for identifying public attitudes toward mask wearing and the reasons for opposition. The results may inform better communication strategies to improve the public perception of wearing masks and, in particular, to specifically address common anti-mask beliefs.

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