Curate from your source library

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Cronycle feeds aggregate content from several sources, combining RSS (a standard for sharing web links), Twitter handles (web links shared on Twitter by these handles) and Cronycle Topics (our own automated curated feeds). This article is about our new tutorial for advanced mode for this aggregation: how to curate from your source library.

In Cronycle, there are indeed several ways to create a feed aggregating sources:

  • From the Create Feed option in Feeds: easy mode recommended if you are relatively new to Cronycle and to curation.
  • From the library of sources: our advanced mode, described here.
  • For Cronycle Topics only: search any Topic in the top search bar or on the Discovery page.
Click or tap on Manage all Sources to access the source library discussed here

When should I curate from the source library?

There are different cases when you may want to use the source library:

  • You imported or want to import a large amount of sources, either via an OPML (if you came from another aggregator) or a connected Twitter account. The library is where the results of the import will appear and where you’ll be able to build feeds.
  • Your team shares sources: read more on how to manage sources collaboratively.
  • Over time, you have manually added a large amount of sources, and reached a point where a spring clean is welcome

What does the source library do?

Cronycle’s source library lists all the sources you have added in feeds and imports. It also lists the Cronycle Topics you are currently using. You can add and remove sources, search and filter the listed sources, create feeds to read, and folders to further organize your sources.

A source library in Cronycle

How to use the source library?

Our tutorial here explains how to:

  • Find the sources I am looking for in the library?
  • Add more sources to my library?
  • Remove sources?
  • Create feeds from sources in the library?
  • Use folders? (and what they are)

We’ll keep you posted!

We are currently working on a new view for folders, to let you view and modify them. Stay tuned:

Collaborate on sources for your content curation

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This post is about how to collaborate on sources when doing curation as a team. Cronycle has a unique feature – Source Pooling – that allows just that for Twitter and RSS sources, as well as Cronycle Topics. It is available with our Enterprise plan.

Why collaborate on sources?

A team collectively curating content can share sources for several reasons. Here are a few:

  • Share the load of scanning for relevant news: ensuring there is no duplication of work
  • Read the same content to have same information for discussions and decisions
  • Help junior or non expert team members get to quality content efficiently
  • Share good sources relevant to another team member’s focus – this was the case for our customer Taylor & Francis

If you use it (or consider doing it) for other reasons, let us know. It can help us improve our solution!

What does source pooling do?

Cronycle users who collaborate together are grouped in worspaces which we call “Organizations”. Within an Organization, team members share several work items: sources, feeds, boards, publishing, tags and contacts (for sending newsletters).

When sources are shared, all users within the Organization can see all the sources of all the contributors. If Vijay adds a source, Kate will see it. And vice versa. Before you take the decision to share sources, you may want to consult your team.

Cronycle users primarily build feeds using sources. There are two ways to do that: either from the feeds (easy mode), or from the library of all sources (advanced mode). In this second case, team members can see the amount of feeds the source is used in, and filter by user who added. Soon, we will add more information for each source (total number across the Organization, list of the feeds and their owners, who added and when).

Each team member can then use the sources they and others added to create custom feeds. They can also discuss how best to structure feeds as a team. Note that we are also working on a separate feature to make feeds shared across several team members. More on that soon!

Note that we don’t allow to share newsletter subscriptions, they remain personal.

How to collaborate on sources?

One needs to be invited by an organization admin to join and work collaboratively on sources, feeds, boards and sources. For Enterprise accounts, this happens on the Admin Console, in the Users page.

When you have taken the decision to start pooling sources, go to the Admin Console. Under Resources, select Sources. There is a simple switch to enable and disable source pooling.

Switch on Source pooling to collaborate on sources for your content curation

Depending on the amount of sources across the organization, loading the whole source library could take a little longer. This is particularly true if you connected a twitter account with a lot of followees, or large OPML files with many RSS links.

Now, go to your Source Library (click on Feeds, and then Manage All Sources in the bottom left). You will see that the source pooling switch is also available on this page.

Collaborate on sources for your content curation from the library of all sources

And that’s it: in the source table above, you can see all the sources from your organization, ready for you to build feeds. We will update this post soon, as we will release changes to make it easier to manage large amounts of sources within a team. To stay tuned:

The Efficacy of Bot Purges

Reading Time: 2 minutesThere’s something rather brutal about the idea of bot purges – perhaps a reflection of the humanity with which we endow human-looking accounts. Twitter’s decision to suspend thousands of accounts last month was less horrific than it sounded: a small attempt to solve a problem which has plagued the platform for over a year now, and has brought into the radar of US and British politicians as an ambivalent if not mercenary hawker of propaganda.

This didn’t stop it from earning the ire of conservative accounts (including some of the more prominent members of the alt-right and related conspiracy theorists), who had found thousands of their followers eviscerated. To them, it represented just another part of the ongoing skirmish with big tech which had attempted to shut them out of the marketplace, or flag their ideas as fake news.

It doesn’t help that at least some of the accounts which Twitter targeted were real conservative commentators rather than strings of code. In fact, it only adds to the ongoing debate about what a bot really is. Granted, there are the most crude examples of accounts which blurt out the same message over and over, but there are plenty of humans who perform similar functions. On the one hand, this arguably says more about the state of Twitter discourse than anything: if your posts look like they’re written by a painfully simple programme, you’re almost certainly not adding a lot to the conversation. The problem only intensifies when we consider that a lot of bot accounts are ‘cyborgs’, partially automated but with a human who can step in as and when necessary.

And then there are sockpuppets – better known as trolls – who voice an opinion for money or patriotism. They’re by no means new or unique to Twitter (Wikipedia has struggled with them for years and years), but at a time when social media has increasingly come under scrutiny, it’s difficult to ignore them. Of course, bot purges can’t capture them: Twitter can only stop automation, not insincere or unethical tweeting.

And therein lies the crux of the problem: purges of bot accounts are like putting a plaster over a serious wound. The people running them will have them back up and running, not least because they’ve proven very quick to adapt to research on automation and integrate it in their strategies. A longer time solution is necessary to restore any meaningful trust in social media. Rather than engaging in heavy-handed crackdowns with little explanation – relying on people not caring enough about what algorithms are really responsible for figuring out who alleged bots are – Twitter could do a lot better with emphasising transparency. Because, at the end of the day, Big Tech has never shown a great concern about its role in affecting democracy, for better or worse: instead, its actions have been dictated by PR concerns.

Moving away from the pedestal of the Philosopher King could do Twitter a little good – and society a whole lot more. Fight bots, by all means, but encourage media education and engage with people too; that’s the way to make the change more than skin-deep.

There is No Solution to the Problem of “Fake News”

Reading Time: 4 minutesIn the aftermath of the 2016 election, the term “fake news”, seldom heard previously, became ubiquitous. This was, of course, no coincidence: the unexpected victory of Donald Trump cried out for an explanation, and invoking the concept was one such attempt by the president’s many critics, who could not bring themselves to face the possibility that he won fairly. As one conservative commentator saw it, “just as progressive ideas were being rejected by voters across the western world, the media suddenly discovered a glitch which explained why. Fake news is the new false consciousness.” But the dissemination of disinformation and propaganda is as old civilization itself. The internet is merely a new means of spreading these, and even then, not especially new. Consider, for instance, the anti-vaccination and “9/11 truth” movements of the preceding decades, and the role played by the internet in amplifying the noises of otherwise small groups of dedicated ideologues or charlatans. So we are still left wondering: why only in the last few years has the term “fake news” entered public discourse?

A possible answer is that the point has been reached at which traditional purveyors of news feel that they no longer have control over broader narratives. Their sounding of the alarm over “fake news” is thus a desperate rallying cry in order to regain this control. Some have drawn an analogy to the invention of the printing press in the 16th century, which also revolutionized the spread of information and led to the Protestant Reformation (and of course, disinformation, such as exaggerated accounts of the horrors of the Spanish Inquisition). From this perspective, it is futile to resist the changing ways in which information spreads. One must adapt or die. In many ways, Donald Trump, who began his presidency fighting off a cascade of “fake news” allegations, including about such petty matters as the size of his inauguration crowd, has done a better job of adapting to the new informational eco-system. Twitter, with its 280–until recently, only 140–character limit, has turned out to be the perfect medium for a president with a reportedly short attention span. He also uses it to bypass the mainstream media in order to reach the public directly with his own message or narrative. And the president has masterfully turned the weapon of “fake news” around, aiming it right back at the media. At the end of 2017, his first year in office, he seemed to relish releasing the “The Highly Anticipated Fake News Awards”, a list of misleading or false anti-Trump news stories undermining the media’s insistence that it is impartial.

For all its faults, however, the mainstream media does have a legitimate point about the dangers of “fake news”. There must be an objective standard against which all purveyors of news are held and there does need to be a common set–or at least core–of facts upon which all rational parties in society can agree. But this is easier said than done, and it is far from obvious that there is a “quick fix” solution to this problem that does not merely favor one set of news purveyors over another, based on criteria other than factual accuracy. For example, many in the US fear that the Federal Communications Commission’s (FCC) proposed changes to “net neutrality” rules will give a few major companies the ability to speed up, slow down or even block access to certain web addresses or content. Comcast, for instance, is simultaneously the largest television broadcasting company, through its National Broadcasting Company (NBC) channel, and the largest internet service provider in the United States. Should the current FCC chairman’s plans to end “net neutrality” succeed, this will put Comcast in a powerful position to regulate–effectively–much of the online media landscape according to its own financial interests as a news organisation.

Social media companies such as Facebook have come under fire for spreading “fake news.” Although Mark Zuckerberg initially argued that Facebook is a tech platform and not a media company per se, he was eventually forced to concede that whatever he had originally intended the company to be, an increasing number of people around the world did in fact get their news primarily from their Facebook newsfeed and that Facebook therefore had a “a responsibility to create an informed community and help build common understanding”. Behind this corporate newspeak must also lie a very real fear that government regulation of Facebook as a media company could end up crippling its business model. If Facebook could be held liable for the spread of false information, it would need to hire thousands of fact checkers to nip this in the bud whenever it occurs, but doing so would be far too costly for the organisation, to say nothing of the practical challenges involved. Thus, it has had to rely on very imperfect “fake news” detection algorithms, and more recently, a deliberate de-emphasis of news altogether, the idea behind this being to return the platform to its original purpose of connecting friends and family.

But it is gradually dawning on many people that the war on “fake news” may be unwinnable. This is because there is no in-principle solution to the age-old philosophical problem of how to know what is true. If anything, this problem has become vastly more difficult now that there is an abundance of information to sort through, presented to us in a non-random–but not necessarily truth-tracking–way. We would all do well, however, to exercise greater skepticism in response to all truth claims, including official ones, such as the vague claim that Russia “hacked the election”. Skepticism does not come naturally to human beings, who are notoriously credulous. One should thus be taught to be skeptical from a young age, and to favor logical consistency and empirical evidence over other considerations when evaluating competing truth claims. This approach falls well short of a real solution, but it may help us individually and collectively to navigate the treacherous ocean of information in which we find ourselves. Hopefully, we will find ways of adjusting to our current information environment and a new equilibrium will emerge from the informational chaos. Cronycle is one platform that is ahead of the curve in this respect: it not only recognizes the problem of information overload, but provides its users with useful tools for finding the trustworthy, high quality content out there in the Wild, Wild Web.

2017 Insights Analysis – GDPR

Reading Time: 3 minutesAfter four years of preparation and debate about GDPR, the EU Parliament approved the regulation in April 2016 to replace an outdated data protection directive from 1995. Today, we have five months to go until the enforcement deadline of General Data Protection Regulation (GDPR) in May 2018. At which, non-compliant organisations can face fines /penalties of up to €20 million or 4% of your global annual turnover, whichever is greater. Encase you are ever in doubt of the time frame, there is a live countdown timer on the EU GDPR website to remind you.


You may be wondering, why the regulation was agreed in the first place? There are two key takeaways as summarised by IT Pro

  • The EU wants to give people more control over how their personal data is used, bearing in mind that many companies like Facebook and Google swap access to people’s data for use of their services. The current legislation was enacted before the internet and cloud technology created new ways of exploiting data, and the GDPR seeks to address that. By strengthening data protection legislation and introducing tougher enforcement measures, the EU hopes to improve trust in the emerging digital economy.
  • Secondly, the EU wants to give businesses a simpler, clearer legal environment in which to operate, making data protection law identical throughout the single market (the EU estimates this will save businesses a collective €2.3 billion a year).


Our newest collaboration between Cronycle and Right Relevance means we can produce insights reports on hot topics to analyse the conversations at any point in time. As GDPR is a key focus for us (and others), we started with this and launched our report this week which you can view here.

Flock graph for GDPR Report 2017

Our report examines the all online conversations during the time period from November 15th to December 4th and along with Right Relevance topics, topical communities’ and articles data. All that data allows us to plot impressive graphs of interactions, with clear communities forming along the lines of nationality and business type. The pale blue cluster, for example, centres on the French data commissioner, CNIL: those accounts orbiting it include French firms and governmental departments.


Our overall findings are that the discussion about GDPR is driven by fear of failing to become compliant, across all kinds of users. Just a glance at our groupings of top trending terms can give a flavour of keywords, which focus on guides and webinars which provide clear guidance on compliance. Discussions about more the more positive side of GDPR, such as greater protection for user information or ethical innovation under the new regulations, appears to be less central at this time.

Using Right Relevance’s data, we can also produce a list of flocks: that’s those accounts which have the most influence in our specific period of research in our specific field. Rather than measuring long-term power, they’re instead a snapshot of the key players at a given moment. They included the British and French data commisioners (the ICO and CNIL), tech journalists, privacy experts like Max Schrems, and trade groups. Conspicuously missing from the table below? Members of Parliament from Britain or France, the countries from which most traffic on GDPR came.

What these flocks show is that it’s not just follower count which gives accounts importance: Laura Kayali (@LauKaya), a Brussels-based reporter, tops out our list but only has 1,524 followers compared to over 37,000 for the ICO (@ICOnews).

Our report also discusses important metrics which are often not covered elsewhere, such as betweenness centrality: how well does an account act as a node for the overall network? Whilst high page rank and betweenness centrality (being a connector here) can be interlinked, that’s not always the case: @LauKaya has a high page rank, but is not a key connector, for example.


Let us know if you have any thoughts or feedback as we are looking to produce a report on GDPR topic at least once a month to keep us all in the loop of conversations.


View the full report

Netflix’s Tweet May Have Been Made Up, But That Shouldn’t Make us Much Happier

Reading Time: 2 minutesThe tweet was meant in good humour undoubtedly: a little post by Netflix, claiming 53 people watched A Christmas Prince 18 days in a row. A light hearted jibe, in the vein of banter so heavily mined by Nando’s. That figure, as some commentators suggested, may well even have been drawn from thin air – a symbolic number, if you like.

And yet the tweet inadvertently underlined an uncomfortable truth about both big data collection offered by services like Netflix or Spotify, and the power which all that information gives algorithms. Whether or not the number is true, Netflix knows a lot about you.

By now, in the wake of Snowden and Wikileaks, you’d be hard pressed to find a citizen in any democracy who didn’t have some inkling of public surveillance.
Yet in some ways, the equally pervasive work of our entertainment apps goes unnoticed.
Perhaps it’s because most of the time, it doesn’t go out of its way to draw our attention to its specificity or scope. The ‘magic sauce’ of recommendations from Spotify is not merely their accuracy, but equally their opacity. Pull back the curtain and instead of the Wizard, you find algorithms and reams and reams of data. Whilst a black box may not satisfy the more paranoid, it offers consumers space to insert a more positive image.
Indeed, as Netflix’s faux pas proved, drawing people’s attention to data collection processes which Hoover up personal (if not private, or strictly speaking sensitive) information is the best way to convince them they’re in the Panopticon.

Of course, there’s nothing to suggest Netflix has weaponised this data in any particular way, beyond recommendations and somewhat unfunny jokes. Even assuming that 53 people really did watch one movie once a day for nigh on three weeks, there’s still the question of what level of identity is available. Are people’s whole life details on offer for any employee to see and laugh at? It would seem unlikely. Far more probable would be data in aggregate – details which are anonymised in essence.

The best outcome to the outrage surrounding the tweet is not to pour on more fuel in social media moral panics, but to use it as a teachable moment. Regardless of how nefarious they are, the amount of information gleaned through entertainment platforms we use daily is immense – something which we as consumers on the other side can forget.

Secondly, it’s important to understand why, to big data analyst is, personal details are less key. Data in combination with other datasets allows them to discover details about a user which would be impossible to glean previously.

Finally, it’s key to acknowledge the centrality of algorithms. Not terrifying cybernetic creatures, they are the lifeblood of so muchblf what we do. Granted, algorithms are by no means neutral – think about risks in police algorithms and sentencing – but they can serve less dubious purposes too.

Big tech is most dangerous when we understand it less. We should be grateful for Netflix’s quite clear blunder: it offers an opportunity for just taking it.

What does Siloed Social Media mean for Politics?

Reading Time: 3 minutesThe old adage for dealing with dealing with online abuse was ‘Don’t feed the trolls’ – a statement based on the premise that they could fundamentally dealt with like offline bullies. By refusing to give them the emotional response and the attention which they crave, the argument went, they would get bored and move off (presumably to bother someone else).

But what does refusing to feed them actually look like, on a platform like Twitter – a space in which it’s easy for celebrities and micro-celebrities to weaponise their fame, turning their followers in far larger numbers and with far greater vehemence than in an offline setting? One answer is to block them, although given that it’s easy enough to make a new account and the sheer volume of the attacks , this can be impractical. Another is to put your account as private – or to go even further and quit it outright.

This was the understandable option taken by the targets of Gamergate, the organised campaign which ostensibly fought for ‘ethics in video game journalism’, but which always looked curiously like a reactionary pushback against criticisms of gaming’s often misogynist culture. Later, actress Leslie Jones would be forced to leave Twitter facing down a mob of a similar sort, targeting her for her ethnicity.

More so than getting an emotional response, this has been the goal of the leaders of the harassment campaigns, such as Milo Yiannopoulos, the former Breitbart employee who was finally permanently removed from Twitter following the campaign against Jones. He wouldn’t be the only ‘martyr’ in the eyes of self-proclaimed freedom fighters. In the wake of the Pizzagate conspiracy theory, rumours began circulation on Twitter about child pornography being hosted by the site by a series of accounts (including current alt-right celebrity, Brittany Pettibone). Having already removed a number of far-right accounts after Trump’s surprise victory, Twitter hastily swung into action, apparently partially to protect its own reputation.

It wouldn’t be the only platform to do so: even Reddit, famously defiant in the face of protests against the mixture of hate speech and borderline felonies on some of its threads, has banned a number (including the once popular r/AltRight). And as would later happen with Twitter, users quickly discovered alternative platforms, whose professed love of freedom went deeper. For Reddit there was Voat, which became central to the Pizzagate ‘investigation’, whilst Twitter got Gab (which also offers an opportunity for recording videos for audiences).

On the one hand, the decision for proponents of particularly loathsome ideologies to migrate from the mainstream space is welcome. A study on Reddit’s work shutting down some of the most controversial and repugnant subreddits suggested that rather than spreading the hate around other threads, most of those displaced tended to pipe down without the community support. Of course, it doesn’t take into account those who moved to platforms like Voat, which have tended to be less open to research from the mainstream establishment.

On the other hand, the practice of banning speech is a plaster for broader societal issues – and not a terribly sticky one in the long term. Although protecting users from campaigns of harassment is common decency (not to mention good business sense), pushing those already heading down dark paths to spaces like Voat seems likely to make their beliefs even more radical. A campaign based around punitive action also plays into their rhetoric of an establishment trying to attack them for violating free speech (gleefully ignoring those who have been forced to leave the arena of free speech out of fear).

The crisis of free speech, although so often imagined as a problem brought on by university safe spaces and ‘snowflake’ culture, is as much – if not more so – the result of a particular strain of conservatism mixed with what Adrienne Massanari dubbed a “toxic technoculture”. The result is a persecution complex which sees any debate as part of a broad attempt to stifle free speech, and a willingness to use whatever tactics necessary to attack opponents (see: fake antifa posters).

There is no easy solution to the problem which we face today – one which looks set to widen as the ‘culture wars’ continue. Forcing those with vile opinions onto alternative spaces no longer looks like the solution, as it simply intensifies their feelings of being stiffed. Allowing them to engage in wanton acts of harassment isn’t either, though: it’s time for tech to take a good look at itself and figure out the third way.

What’s all the fuss about content filtering?

Reading Time: 3 minutesRSS Reader

A colleague of mine asked me this question a while ago when we were discussing the problem of the facebook algorithm. Here’s how it works: facebook shows you the news that it thinks you’re most likely to interact with. After all, if your second cousin posts endless pictures of things you’re not interested in, it makes sense for facebook to dial back on his updates and dial in some more interesting content from your sister, who posts news articles that keep you informed.

The problem is that, although this sounds fine in principle, in practise it creates a very different environment to the one you would expect. Often news is dialed back to make way for easy ‘clickbait’ type content, or videos are prioritised because they’re more engaging.

So, a computer decides what you get to see and what it will hide. And computers – while they can be incredibly smart – are not always going to make the same decisions as humans.

Over on GigaOm this week, Matthew Ingrams discussed the merits of Twitter vs facebook as a source for news. In the wake of the shocking incidents in Ferguson, Missouri, some people were surprised to see facebook almost completely devoid of news. Twitter was filled with live updates, eye-witness reports, photos and videos of events as they unfolded. Facebook: almost nothing. Why so different? While Facebook has a filtering algorithm constantly trying to guess what you’ll respond to, Twitter shows you everything from the people you follow, so you’re going to receive all the updates from people you follow in your timeline, whether you’re likely to retweet them or not. While Facebook is trying to be your personal shopper, hand-picking items it knows you’ll like, Twitter shows you all of the products in the shop.

The Twitter model is great, for a while, and gets around this initial problem of algorithmic filtering. Unfortunately, because you see everything, it can be incredibly difficult to keep track. We humans are, and always have been, fans of filtering and sorting. Even before the internet age, when we were bombarded with data from all sides, we’d rarely seek out everything – choosing instead to curate our sources (by buying a specific newspaper, or watching a particular news channel, for instance). To continue the shopping analogy, Twitter gives you the option of seeing every product, but there are so many on such a fast-moving conveyor belt you barely have time to examine something before twenty other things have gone whizzing past.

Can there be a balance? Well, there are a couple of possible ways to solve this problem. Method one – the one which facebook is trying is to simply make automated filtering better. Facebook tries to improve the algorithms so that they don’t get too one-sided, or churn out too much similar content – their priority is to keep you on the site and get you using it a lot, so ultimately if their algorithm is stopping you from doing that they’ll improve it. Twitter is also tweaking what shows up automatically on the timeline – recent changes to how ‘favourites’ are displayed have met with opposition from users, but it’s one of many experiments to try and make Twitter feel like a more  ‘usable’ place. To engage new users, Twitter is trying to introduce a form of content curation that makes it easier for people to find what they love.

Will either of these techniques work? Possibly. But one of the reasons we started Cronycle is that we think there’s a better option. Not better algorithmic filtering – because it will ultimately always run into the ‘machine’ problem – but applying a layer of human curation to the deluge of content.

Human curation is the solution to algorithmic content filtering

Cronycle takes all of your sources (the RSS feeds you subscribe to, the Twitter accounts you follow) and indexes all of the important content (anything that includes a link or image is pulled through). You can then filter and curate those posts into a collection based on criteria you choose – you can add a filter for the latest breaking news story, for example, filtering in only content from the news teams you really trust. You could have a different collection for updates on a particular area of industry, which gathers articles from expert sources that you’ve chosen yourself.

There’s a certain amount of machine help here, for sure – you’re not creating your own newspaper. Cronycle is useful because it helps you cut through the noise, and prevents you having to scroll through reams of irrelevant content just to get updates on the latest news story or blog post. But the key difference between Cronycle and any algorithmic filtering system is that you won’t run into the ‘facebook problem’ – machines pushing you content based on simplistic models of your behaviour. You choose the sources, you set the filters, and Cronycle indexes that content. Unlike facebook, it won’t ever second guess you.

Published on 21.08.2014 by Marina Cheale

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