The footprint of campaign strategies in Farsi Twitter: A case for 2021 Iranian presidential election.
Ontology highlight
ABSTRACT:
SUBMITTER: Mohammadi S
PROVIDER: S-EPMC9333222 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Donald Trump's 2016 win despite failing to carry the popular vote has raised concern that 2020 would also see a mismatch between the winner of the popular vote and the winner of the Electoral College. This paper shows how to forecast the electoral vote in 2020 taking into account the unknown popular vote and the configuration of state voting in 2016. We note that 2016 was a statistical outlier. The potential Electoral College bias was slimmer in the past and not always favoring the Republican candidate. We show that in past presidential elections, difference among states in their presidential voting is solely a function of the states' most recent presidential voting (plus new shocks); earlier history does not matter. Based on thousands of simulations, our research suggests that the bias in 2020 probably will favor Trump again but to a lesser degree than in 2016. The range of possible outcomes is sufficiently wide, however, to even include some possibility that Joseph Biden could win in the Electoral College while barely losing the popular vote.
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Project description:BackgroundThe 2016 presidential election and the controversial policy agenda of its victor have raised concerns about how the election may have impacted mental health.ObjectiveAssess how mental health changed from before to after the November 2016 election and how trends differed in states that voted for Donald Trump versus Hillary Clinton.DesignPre- versus post-election study using monthly cross-sectional survey data.ParticipantsA total of 499,201 adults surveyed in the Behavioral Risk Factor Surveillance System from May 2016 to May 2017.ExposureResidence in a state that voted for Trump versus state that voted for Clinton and the candidate's margin of victory in the state.Main measuresSelf-reported days of poor mental health in the last 30 days and depression rate.Key resultsCompared to October 2016, the mean days of poor mental health in the last 30 days per adult rose from 3.35 to 3.85 in December 2016 in Clinton states (0.50 days difference, p = 0.005) but remained statistically unchanged in Trump states, moving from 3.94 to 3.78 days (- 0.17 difference, p = 0.308). The rises in poor mental health days in Clinton states were driven by older adults, women, and white individuals. The depression rate in Clinton states began rising in January 2017. A 10-percentage point higher margin of victory for Clinton in a state predicted 0.41 more days of poor mental health per adult in December 2016 on average (p = 0.001).ConclusionsIn states that voted for Clinton, there were 54.6 million more days of poor mental health among adults in December 2016, the month following the election, compared to October 2016. Clinicians should consider that elections could cause at least transitory increases in poor mental health and tailor patient care accordingly, especially with the 2020 election upon us.
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Project description:ObjectiveResearch suggests that sociopolitical stressors connected with the 2016 presidential election were associated with increases in preterm birth among Latina women. This study determined whether periviable births (<26 weeks gestation), which exhibit extremely high rates of infant morbidity and mortality, among US Latina women increased above expected levels after the 2016 US presidential election.MethodsWe assigned singleton live births among Latina and non-Latina white women in the US to 96 monthly conception cohorts conceived from January 2009 through December 2016. We constructed risk ratios by dividing the rate of periviable birth among Latina women by the rate among non-Latina white women. We used time-series methods to determine if the risk ratio of periviable births in cohorts conceived by Latina women and exposed to the election of 2016 exceeded those expected from autocorrelation and calendar effects.ResultsWe found an outlying sequence of risk ratios among Latina women starting with the cohort conceived in April and ending with that conceived in November 2016. Increases in the ratios ranged from 0.07 above an expected of 1.61 for the cohort conceived in June, to 0.39 above an expected of 1.27 for the cohort conceived in April.ConclusionWe find that pregnancies in gestation at the time of the 2016 election among Latina women yielded more than expected periviable births. These findings support the argument that the prospect of anti-immigrant policies promised by the Trump campaign sufficiently stressed Latina women to affect the timing of birth.
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