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Conventional wisdom assumes that increased censorship will strictly decrease access to information. We delineate circumstances when increases in censorship expand access to information for a substantial subset of the population. When governments suddenly impose censorship on previously uncensored information, citizens accustomed to acquiring this information will be incentivized to learn methods of censorship evasion. These evasion tools provide continued access to the newly blocked information—and also extend users' ability to access information that has long been censored. We illustrate this phenomenon using millions of individual-level actions of social media users in China before and after the block of Instagram. We show that the block inspired millions of Chinese users to acquire virtual private networks, and that these users subsequently joined censored websites like Twitter and Facebook. Despite initially being apolitical, these new users began browsing blocked political pages on Wikipedia, following Chinese political activists on Twitter, and discussing highly politicized topics such as opposition protests in Hong Kong.

Past research suggests that spouses influence one another to vote, but it relies almost exclusively on correlation in turnout. It is therefore difficult to establish whether spouses mobilize each other or tend to marry similar others. Here, we test the dependency hypothesis by examining voting behavior before and after the death of a spouse. We link nearly six million California voter records to Social Security death records and use both coarsened exact matching and multiple cohort comparison to estimate the effects of spousal loss. The results show that after turnout rates stabilize, widowed individuals vote nine percentage points fewer than they would had their spouse still been living; the results also suggest that this change may persist indefinitely. Variations in this 'widowhood effect' on voting support a social-isolation explanation for the drop in turnout. Adapted from the source document.

Past research suggests that spouses influence one another to vote, but it relies almost exclusively on correlation in turnout. It is therefore difficult to establish whether spouses mobilize each other or tend to marry similar others. Here, we test the dependency hypothesis by examining voting behavior before and after the death of a spouse. We link nearly six million California voter records to Social Security death records and use both coarsened exact matching and multiple cohort comparison to estimate the effects of spousal loss. The results show that after turnout rates stabilize, widowed individuals vote nine percentage points fewer than they would had their spouse still been living; the results also suggest that this change may persist indefinitely. Variations in this "widowhood effect" on voting support a social‐isolation explanation for the drop in turnout.

Crisis motivates people to track news closely, and this increased engagement can expose individuals to politically sensitive information unrelated to the initial crisis. We use the case of the COVID-19 outbreak in China to examine how crisis affects information seeking in countries that normally exert significant control over access to media. The crisis spurred censorship circumvention and access to international news and political content on websites blocked in China. Once individuals circumvented censorship, they not only received more information about the crisis itself but also accessed unrelated information that the regime has long censored. Using comparisons to democratic and other authoritarian countries also affected by early outbreaks, the findings suggest that people blocked from accessing information most of the time might disproportionately and collectively access that long-hidden information during a crisis. Evaluations resulting from this access, negative or positive for a government, might draw on both current events and censored history.

Social media data can provide new insights into political phenomena, but users do not always represent people, posts and accounts are not typically linked to demographic variables for use as statistical controls or in subgroup comparisons, and activities on social media can be difficult to interpret. For data scientists, adding demographic variables and comparisons to closed-ended survey responses have the potential to improve interpretations of inferences drawn from social media—for example, through comparisons of online expressions and survey responses, and by assessing associations with offline outcomes like voting. For survey methodologists, adding social media data to surveys allows for rich behavioral measurements, including comparisons of public expressions with attitudes elicited in a structured survey. Here, we evaluate two popular forms of linkages—administrative and survey—focusing on two questions: How does the method of creating a sample of Twitter users affect its behavioral and demographic profile? What are the relative advantages of each of these methods? Our analyses illustrate where and to what extent the sample based on administrative data diverges in demographic and partisan composition from surveyed Twitter users who report being registered to vote. Despite demographic differences, each linkage method results in behaviorally similar samples, especially in activity levels; however, conventionally sized surveys are likely to lack the statistical power to study subgroups and heterogeneity (e.g., comparing conversations of Democrats and Republicans) within even highly salient political topics. We conclude by developing general recommendations for researchers looking to study social media by linking accounts with external benchmark data sources.