By 2017, we have found in other research that 66 percent of a sample of major European newspapers operate pay models, and prominent digital-born news publishers across the continent (including De Correspondent, El Diario, and the pioneering Mediapart) operate paid or membership models. Broadcasters generally don’t (though CNN plans to introducing digital subscriptions), but they benefit from still significant offline revenues and can treat online as a loss-leading brand extension.Most of the digital-born news publishers who have sought international expansion have neither subscribers, members, nor offline revenues to sustain their operations. They rely on digital advertising. As Jean-Christophe Potocki, general manager at HuffPost France told us: “If we don’t fight this battle, given our model, we’re dead. Diversification is to provide extra, but our model is advertising and we need to fight it directly.”Not all of these outlets will win this fight and be able to sustain itself on advertising alone (just as not every newspaper or niche news site will make pay models work). The challenges they face are clear, and include:low average revenues per user, especially with the move from desktop to mobile accelerating;the rise of programmatic advertising, widely seen as depressing CPMs for display advertising;the competition from large technology companies, most significantly Google and Facebook, that attract a large share of online advertising;the use of ad-blockers as users are frustrated by intrusive ads and long load times.
Gobo retrieves posts from people you follow on Twitter and Facebook and analyzes them using simple machine learning-based filters. You can set those filters — seriousness, rudeness, virality, gender and brands — to eliminate some posts from your feed. The “politics” slider works differently, “filtering in”, instead of “filtering out” — if you set the slider towards “lots of perspectives”, our “news echo” algorithm will start adding in posts from media outlets that you likely don’t read every day.
Facebook Explore Feed is rolling out globally this week. Most people around the world can see it in their bookmarks and they can discover new content here. But in Slovakia, Sri Lanka, Serbia, Bolivia, Guatemala and Cambodia it works differently: all posts by pages are moved from newsfeed to Explore Feed. In main newsfeed are now just friend and sponsored posts. Yes, you log into Facebook and you can see only posts from your friends and ads. You have to click on Explore Feed to see posts from pages you follo
Facebook may make it harder for people to see publishers’ stories, unless those publishers pay to promote them. As part of a new test in six countries, Facebook is taking content from publishers and businesses out of its main feed. Instead, those posts will exist in a separate, hard-to-find feed that Facebook recently launched for discovering new stuff, called the “Explore Feed.”
The Web is a key space for civic debate and the current battleground for protecting freedom of expression. However, since its development, the Web has steadily evolved into an ecosystem of large, corporate-controlled mega-platforms which intermediate speech online. In many ways this has been a positive development; these platforms improved usability and enabled billions of people to publish and discover content without having to become experts on the Web’s intricate protocols.But in other ways this development is alarming. Just a few large platforms drive most traffic to online news sources in the U.S., and thus have enormous influence over what sources of information the public consumes on a daily basis. The existence of these consolidated points of control is troubling for many reasons. A small number of stakeholders end up having outsized influence over the content the public can create and consume. This leads to problems ranging from censorship at the behest of national governments to more subtle, perhaps even unintentional, bias in the curation of content users see based on opaque, unaudited curation algorithms. The platforms that host our networked public sphere and inform us about the world are unelected, unaccountable, and often impossible to audit or oversee.
At the same time, there is growing excitement around the area of decentralized systems, which have grown in prominence over the past decade thanks to the popularity of the cryptocurrency Bitcoin. Bitcoin is a payment system that has no central points of control, and uses a novel peer-to-peer network protocol to agree on a distributed ledger of transactions, the blockchain. Bitcoin paints a picture of a world where untrusted networks of computers can coordinate to provide important infrastructure, like verifiable identity and distributed storage. Advocates of these decentralized systems propose related technology as the way forward to “re-decentralize” the Web, by shifting publishing and discovery out of the hands of a few corporations, and back into the hands of users. These types of code-based, structural interventions are appealing because in theory, they are less corruptible and resistant to corporate or political regulation. Surprisingly, low-level, decentralized systems don’t necessarily translate into decreased market consolidation around user-facing mega-platforms.In this report, we explore two important ways structurally decentralized systems could help address the risks of mega-platform consolidation: First, these systems can help users directly publish and discover content directly, without intermediaries, and thus without censorship. All of the systems we evaluate advertise censorship-resistance as a major benefit. Second, these systems could indirectly enable greater competition and user choice, by lowering the barrier to entry for new platforms. As it stands, it is difficult for users to switch between platforms (they must recreate all their data when moving to a new service) and most mega-platforms do not interoperate, so switching means leaving behind your social network. Some systems we evaluate directly address the issues of data portability and interoperability in an effort to support greater competition.We offer case studies of the following decentralized publishing projects:Freedom Box, a system for personal publishingDiaspora, a federated social networkMastodon, a federated Twitter-like serviceBlockstack, a distributed system for online identity servicesIPFS (Interplanetary File System), a distributed storage service with a proposed mechanism to incentivize resource sharingSolid (Social Linked Data), a linked-data protocol that could act as a back-end for data sharing between social media networksAppcoins, a digital currency framework that enables users to financially participate in ownership of platforms and protocolsSteemit, an online community that uses an appcoin to incentivize development and community participation in a social networkConsidering these projects as a whole, we found a robust and fertile community of experimenters developing promising software. Many of the projects in this report are working on deeply exciting new ideas. Easy to use, peer-to-peer distributed storage systems change the landscape for content censorship and archiving. Appcoins may transform how new projects are launched online, making it possible to fund open-source development teams focused on developing shared protocols instead of independent companies. There is also a renewed interest in creating interoperable standards and protocols that can cross platforms.However, we have reason to doubt that these decentralized systems alone will address the problems of exclusion and bias caused by today’s mega-platforms. For example, distributed, censorship-resistant storage does not help address problems related to bias in curation algorithms – content that doesn’t appear at the top of your feed might as well be invisible, even if it’s technically
Source: The Decentralized Web
Designing robust reward mechanisms to curate content that keeps people informed rather than entertained remains a problem. If distributed platforms could solve it, they could theoretically tackle media challenges like echo chambers and filter bubbles, but such dilemmas still present a serious challenge for new systems.
How significant is algorithmic personalization in searches for political parties and candidates?
After popularizing sensational headlines and taking your news feed by storm, Upworthy seemingly fell off a cliff. Its story reveals just as much about Facebook as it does about why we click.
Researchers from London School of Economics report about their ongoing research into political targeting on Facebook in the UK (the research is done in collaboration with WhoTargetsMe, a browser extension to measure political targeting on Facebook):
As we made clear in our first two posts, our analysis here is exploratory. It is, for example, unclear to what extent our dataset is representative of Conservatives’ online advertising throughout this campaign, and the WhoTargetsMe sample of potential voters, from whose Facebook feeds our data is scraped, may be skewed.
Bearing in mind these problems, we can say that, of the 820 exposures to ads paid for by Conservatives that we analysed, 28% (or 232 items) attacked Corbyn using facts that appear to be false or are clearly manipulated to confound the reader – and sometimes both.
Generally, Conservatives used 73% (598) of its 820 ads exposed in our sample to attack Corbyn. They are not, of course, the only ones targeting opponents. As we have shown, both Labour and Lib Dems have done the same. However, while ads by these other parties conveyed simplifying messages, portraying adversaries as weak, immoral or pro-elite, we couldn’t find, at least in our samples, pieces by them using baseless or misleading facts.