👓 On Twitter, Students Want to Know: How Many Retweets for a Full-Ride Scholarship? | The Chronicle

Read On Twitter, Students Want to Know: How Many Retweets for a Full-Ride Scholarship? (The Chronicle of Higher Education)
In the self-serving subculture of retweeting for fame, some universities have been hit with repeated requests for free tuition — if a prospective student can spur a storm of retweets.

👓 Are Targeted Ads Stalking You? Here’s How to Make Them Stop | New York Times

Read Are Targeted Ads Stalking You? Here’s How to Make Them Stop (nytimes.com)
Ever been haunted by an online ad for an item you researched or bought? Targeted ads were designed to follow you around everywhere. Here’s how to banish them.

👓 GDPR will pop the adtech bubble | Doc Searls

Read GDPR will pop the adtech bubble by Doc SearlsDoc Searls (Doc Searls Weblog)

Since tracking people took off in the late ’00s, adtech has grown to become a four-dimensional shell game played by hundreds (or, if you include martech, thousands) of companies, none of which can see the whole mess, or can control the fraud, malware and other forms of bad acting that thrive in the midst of it.

And that’s on top of the main problem: tracking people without their knowledge, approval or a court order is just flat-out wrong. The fact that it can be done is no excuse. Nor is the monstrous sum of money made by it.

Without adtech, the EU’s GDPR (General Data Protection Regulation) would never have happened. But the GDPR did happen, and as a result websites all over the world are suddenly posting notices about their changed privacy policies, use of cookies, and opt-in choices for “relevant” or “interest-based” (translation: tracking-based) advertising. Email lists are doing the same kinds of things.

Some interesting thought and analysis here on the pending death of adtech with the dawn of GDPR in the EU. I’m hoping that this might help bring about a more humanistic internet as a result.

There’s a lot to unpack here, but it looks like some tremendously valuable links and resources embedded in this article as well. I’ll have to circle back around to both re-read this and delve more deeply in to these pointers.

🔖 Identifying Modes of User Engagement with Online News and Their Relationship to Information Gain in Text by Nir Grinberg

Bookmarked Identifying Modes of User Engagement with Online News and Their Relationship to Information Gain in Text by Nir GrinbergNir Grinberg (dl.acm.org)
Prior work established the benefits of server-recorded user engagement measures (e.g. clickthrough rates) for improving the results of search engines and recommendation systems. Client-side measures of post-click behavior received relatively little attention despite the fact that publishers have now the ability to measure how millions of people interact with their content at a fine resolution using client-side logging. In this study, we examine patterns of user engagement in a large, client-side log dataset of over 7.7 million page views (including both mobile and non-mobile devices) of 66,821 news articles from seven popular news publishers. For each page view we use three summary statistics: dwell time, the furthest position the user reached on the page, and the amount of interaction with the page through any form of input (touch, mouse move, etc.). We show that simple transformations on these summary statistics reveal six prototypical modes of reading that range from scanning to extensive reading and persist across sites. Furthermore, we develop a novel measure of information gain in text to capture the development of ideas within the body of articles and investigate how information gain relates to the engagement with articles. Finally, we show that our new measure of information gain is particularly useful for predicting reading of news articles before publication, and that the measure captures unique information not available otherwise.
Bookmarked to read as result of reading The five ways we read online (and what publishers can do to encourage the “good” ones).

[.pdf] copy available on author’s site.

👓 The five ways we read online (and what publishers can do to encourage the “good” ones) | Nieman Lab

Read The five ways we read online (and what publishers can do to encourage the “good” ones) by Laura Hazard Owen (Nieman Lab)
New metrics specifically for news articles.
I love that there’s research1 going on in this area and it portends some potentially great things for reading, but the devil’s advocate in me can also see a lot of adtech people salivating over the potential dark patterns lurking in such research. I can almost guarantee that Facebook is salivating over this, though to be honest, they’ve really pioneered the field haven’t they, just in a much smaller area of use. Of course I’m also curious if they did or are planning any research in how people read content on social media?

I wonder what it would look/feel like to take each of these modalities and apply them individually for long periods of time to everything one read? Or to use them in rotation regardless of the subject being read? Or other permutations? I suppose in general I like to read how I like to read, but now I’m going to be more conscious of what and how I’m doing it all.

References

1.
Grinberg N. Identifying Modes of User Engagement with Online News and Their Relationship to Information Gain in Text. WWW ’18 Proceedings of the 2018 World Wide Web Conference. https://dl.acm.org/citation.cfm?id=3186180. Published April 23, 2018. Accessed April 27, 2018.

👓 Why Are Newspaper Websites So Horrible? | City Lab

Read Why Are Newspaper Websites So Horrible? by Andrew Zaleski (CityLab)
Blame Google, for a start.
Nothing great or new here. Also no real solutions, though knowing some of the history and the problems, does help suggest possible solutions.

h/t to @ajzaleski, bookmarked on April 19, 2018 at 01:17PM

🎧 Gillmor Gang 05.13.17: Doc Soup | Tech Crunch

Listened to Gillmor Gang: Doc Soup by Steve Gillmor, Doc Searls, Keith Teare, Frank Radice from TechCrunch

Recorded live Saturday, May 13, 2017. The Gang takes nothing off the table as Doc describes a near future of personal APIs and CustomerTech.

Keith outlines an excellent thesis about media moving from “one to many” to increasingly becoming “one to one”. It points out the issue for areas like journalism, which can become so individualized, and democracy which often rely on being able to see the messages that are given out to the masses being consistent. One of the issues with Facebook and the Cambridge Analytica problem is that many people were getting algrorithmic customized messages (true or not) that had the ability to nudge them in certain directions. This creates a lot more control on the part of major corporations which would have been far less likely when broadcasting the exact same message to millions. In the latter case, the message for the masses can be discussed, analyzed, picked apart, and dealt with because it is known. In the former case, no one knows what the message was except for the person who received it and it’s far less likely that they analyzed and discussed it in the same way that it would have been previously.

In the last portion of the show, Doc leads with some discussion about identity and privacy from the buyer’s perspective. Companies selling widgets don’t necessarily need to collect massive amounts of data about us to sell widgets. It’s the seller’s perspective and the over-reliance on advertising which has created the capitalism surveillance state we’re sadly living within now.

In the closing minutes of the show Steve re-iterated that the show was a podcast, but that it’s now all about streaming and as such, there is no longer an audio podcast version of the show. I’ll have something to say about this shortly for those looking for alternatives, because this just drives me crazy…

📺 Zeynep Tufekci: We’re building a dystopia just to make people click on ads | TED

Watched We're building a dystopia just to make people click on ads by Zeynep TufekciZeynep Tufekci from ted.com

We're building an artificial intelligence-powered dystopia, one click at a time, says techno-sociologist Zeynep Tufekci. In an eye-opening talk, she details how the same algorithms companies like Facebook, Google and Amazon use to get you to click on ads are also used to organize your access to political and social information. And the machines aren't even the real threat. What we need to understand is how the powerful might use AI to control us -- and what we can do in response.