Category: Data-Labor-Technology Stories

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“The Sell Sider” is a column written by the sell side of the digital media community. Today’s column is written by Erik Requidan, vice president of programmatic strategy at Intermarkets. For many, the news has not brought much joy in the last year; it seems to have brought more controversy than ever before. That’s created… Continue reading »

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Mark Zuckerberg recently shared that Facebook is revamping the news feed to prioritize content from friends over content from brands, businesses and publishers. Facebook’s stock price dropped 5 percent immediately following the announcement. This change should not be taken lightly. While Facebook does update its news feed algorithms regularly, as Adam Mosseri, Facebook’s news feed…

Animojis are one of the more buzzed-about features of iPhone X. The phone’s TrueDepth camera analyzes your facial expressions and mirrors them in a dozen different Animojis, creating little animations that you can send as texts within the Messages app. Apple is pushing the feature (four new Animojis are coming to iOS 11.3 this spring)…

In January 2016, Nielsen added data from Facebook to its already existing Nielsen TV Twitter Ratings, rechristening the offering Nielsen Social Content Ratings. Nick Grudin (now vice president of media partnerships) and Brian Robinson (now director, media partnerships analytics) said in a blog post at the time that Instagram would be added to Nielsen Social…

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Welcome to AdExchanger Talks, a podcast focused on data-driven marketing. Subscribe here. The mobile app space remains a silo, thanks to the unique logic of installs and post-install engagement. But that will inevitably change as cross-device identity and omnichannel measurement take hold. Our guest on the podcast this week, Tune CEO Peter Hamilton, positioned his company early… Continue reading »

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Several of the adjustment approaches used in this study require a dataset that is highly representative of the U.S. adult population. This dataset essentially serves as a reference for making the survey at hand (e.g., the online opt-in samples) more representative. When selecting a population dataset, researchers typically use a large, federal benchmark dataset such […]

Raking Raked weights were created using the marginal distributions of the adjustment variables as derived from the synthetic population dataset, along with all two-way interactions of collapsed versions of the demographic variables. For the interactions, the 18-24 and 25-34 age categories were combined, the less than high school and high school graduate categories were combined, […]

This study, sponsored by Pew Research Center, used online opt-in survey data collected by three commercial vendors. Each vendor provided their own sample and administered the survey themselves, based on a common questionnaire. While no vendor makes the claim that that these are probability-based samples, they are intended to represent the noninstitutionalized U.S. adult population, […]

This report was made possible by The Pew Charitable Trusts. Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. This report is a collaborative effort based on the input and analysis of the following individuals: Research team Andrew Mercer, Senior Research Methodologist Arnold Lau, Research Analyst Courtney Kennedy, Director, Survey […]

While previous sections of this report have focused on the kinds of systematic biases that may be the largest worry when it comes to public opinion polls, the variance (or precision) of estimates is important as well. Pollsters most commonly talk about precision in terms of the “margin of error” (MOE), which describes how much […]