Numbers, Facts and Trends Shaping Your World

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  • report

    2. Highly engaged partisans have starkly different views of the news media

    The public’s level of engagement – both politically and with the news – adds another dimension to partisans’ evaluations of the news media. Divides within the parties once again emerge, and partisans who are highly engaged are the most polarized in a range of views of the news media. In general, Republicans and Republican leaners […]

  • quiz

    Digital knowledge quiz (2019)

    Test your knowledge on digital topics and terms by taking our 10-question quiz, then see how your answers compare to our nationally-representative survey.

  • report

    A Field Guide to Polling: Election 2020 Edition

    While survey research in the United States is a year-round undertaking, the public’s focus on polling is never more intense than during the run-up to a presidential election.

  • report

    Appendix: Classifying European political parties

    Classifying parties as populist Although experts generally agree that populist political leaders or parties display high levels of anti-elitism, definitions of populism vary. We use three measures to classify populist parties: anti-elite ratings from the 2017 Chapel Hill Expert Survey (CHES), Inglehart and Norris’s populism party scale and The PopuList. We define a party as […]

  • report

    4. Parents’ attitudes – and experiences – related to digital technology

    In today’s digitally connected world, parents have to manage their own relationship with the internet and mobile devices, along with managing their children’s use of and exposure to the same technology. This brings with it a host of both benefits and challenges. Parents, which includes those who have at least one child under the age […]

  • data essay

    How does a computer ‘see’ gender?

    A computer can be trained to predict whether an image shows a man or a woman. Can you identify which parts of the face are most essential to the computer’s decision?

  • report

    Appendix D: Older people, more affluent tend to have fewer hardships using mobile devices

    In this report, we explored demographic differences associated with mobile phone use and hardships. To do this, we used a hierarchical linear regression to predict the total number of hardships people experience, controlling for other factors that affect mobile phone use. We used Stata’s mixed function to estimate a weighted, mixed-effect linear model with random […]