From Pew Research Center: Methods <[email protected]>
Subject Using machine vision to understand gender in images
Date September 5, 2019 3:02 PM
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Pew Research Center


Thursday, September 5, 2019

Methods


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** Using machine vision to understand gender in images ([link removed])
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In recent years, computer-driven image recognition systems that automatically recognize and classify human subjects have become increasingly widespread. A form of machine intelligence called deep learning is the basis of these image recognition systems, as well as many other artificial intelligence efforts. In a new data essay ([link removed]) , Pew Research Center’s Data Labs team describes how we designed a deep learning system capable of identifying men and women in digital images to conduct our studies focused on gender representation in Google image search results ([link removed]) and images from news posts on Facebook ([link removed]) . Learn about the facial features machine learning models rely on to assess gender with our interactive tool
([link removed]) and read our new report ([link removed]) about Americans’ views of facial recognition technology.



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** How is polling done around the world? ([link removed])
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The methodology behind Pew Research Center’s international surveys ([link removed]) can vary from country to country, and what works in one place might not work in another. In the latest installment ([link removed]) of our Methods 101 video series, we look at some of the challenges of international polling, including government restrictions on survey work, political or social instability that can make it unsafe for interviewers to do their jobs, and a lack of qualified partners who can help administer surveys locally.



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** A week in the life of popular YouTube channels ([link removed])
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As part of a continuing effort to understand the digital ecosystem and the flow of information online, Pew Research Center published a new report ([link removed]) based on a comprehensive analysis of YouTube channels with at least 250,000 subscribers and the videos they posted over the first week of 2019. The report builds on a 2018 study of YouTube’s recommendation engine ([link removed]) and is the first Center analysis to systematically assess the content of YouTube videos, using both machine learning (to identify English-language videos) and online crowdsourcing ([link removed]) (to understand the topic and themes of each video).



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** How Pew Research Center counts unauthorized immigrants in the U.S. ([link removed])
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The way Pew Research Center experts calculate the estimated number of unauthorized immigrants ([link removed]) in the United States is the product of decades of work by Senior Demographer Jeffrey S. Passel, along with former colleagues at the U.S. Census Bureau and the Urban Institute. On the Center's Fact Tank blog, Passel addresses some common questions ([link removed]) about the research techniques used to derive the unauthorized immigrant population estimate.

* Video: Is the number of unauthorized immigrants living in the U.S. declining? ([link removed])



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** Why survey estimates of the number of Americans online don’t always agree ([link removed])
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How many U.S. adults use the internet? While there is a lot of information available from large, high response rate federal surveys (as well as from surveys conducted by Pew Research Center ([link removed]) and other organizations), these different sources of information measure internet use in ways that can be tricky to reconcile. In a recent Fact Tank post ([link removed]) , we explore why internet use estimates differ between surveys and explain how our research experts approach the question.



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** How we check numbers and facts at Pew Research Center ([link removed])
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All of the material we release at Pew Research Center goes through a rigorous verification process we call a “number check.” It's called a number check, but we check much more than the numbers. Although there are slight differences in the process depending on the nature of the data used in a given report, the process is rigorous no matter what we're checking. In a recent Decoded post ([link removed]) , we provide a step-by-step walkthrough of how one of our researchers number checks a piece of domestically focused survey research.



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** Happy birthday, Decoded! 🎂 ([link removed])
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Pew Research Center’s Decoded ([link removed]) blog focuses on the “how” behind our numbers. The blog features content ranging from survey methods to data science to data visualization, and allows researchers to build on and engage with our work.

We celebrated the first birthday of Decoded in June with a thread on Twitter ([link removed]) highlighting some of the most popular posts from the past year. These included the first installation in our series on analyzing Center survey data in R ([link removed]) , a post on how we use application programming interfaces (APIs) ([link removed]) to collect website data, and a write-up from the Center’s data visualization design team on using small multiple charts ([link removed]) .

Explore some of our latest posts:

* Who's home and who isn't? The challenges of conducting face-to-face interviews in Jordan ([link removed])
* Working with geography in survey data ([link removed])
* Using tidyverse tools with Pew Research Center survey data in R ([link removed])
* Lessons learned from more than 20 years of asking about Americans' online news habits ([link removed])
* How public & private Twitter users in the U.S. compare – and why it might matter for research ([link removed])




** Featured Datasets
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Fall 2017 Media and Politics in Western Europe Survey ([link removed])

Survey of eight western European countries conducted Oct. 30–Dec. 20, 2017.


2018 National Survey of Latinos ([link removed])

Survey conducted July 26–Sept. 9, 2018 among a nationally representative sample of 1,501 U.S. Latino respondents ages 18 and older.


American Trends Panel Wave 33 (space exploration, environmental protection) ([link removed])

Survey conducted March 27–April 9, 2018 among 2,541 respondents.



** Job Openings
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Temporary Content Analyst, Journalism ([link removed])


Research Associate, Global Religious Demography ([link removed])


Associate Digital Producer ([link removed])





** Support Pew Research Center
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Please support Pew Research Center with a contribution on the Center’s behalf to our parent organization, The Pew Charitable Trusts.

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Pew Research Center is a nonpartisan fact tank. As a neutral source of data and analysis, Pew Research Center does not take policy positions.


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