👓 All the URLs you need to block to *actually* stop using Facebook | Quartz

Just by the bulk of URLs, this gives a more serious view of just how ingrained Facebook is in tracking your online life.

📺 Zeynep Tufekci: Online social change: easy to organize, hard to win | TED

Watched Online social change: easy to organize, hard to win by Zeynep TufekciZeynep Tufekci from ted.com

Today, a single email can launch a worldwide movement. But as sociologist Zeynep Tufekci suggests, even though online activism is easy to grow, it often doesn't last. Why? She compares modern movements -- Gezi, Ukraine, Hong Kong -- to the civil rights movement of the 1960s, and uncovers a surprising benefit of organizing protest movements the way it happened before Twitter.

Replied to a post by Jeff Doshna (facebook.com)
I have a real problem. I HATE FACEBOOK, what they are doing with our data, how they control access to information and news for millions of people, and the fact that they've insinuated themselves into every aspect of our lives.

So I'm inclined to walk away from it entirely.

But....

There's real information on here that I need, about people I care about, about things going on in my communities, and keeping connected with folks who've been part of my life over the years.

So, what to do?
You can add people to custom Facebook lists and just read those, but then you’re not necessarily getting all the data you want given the Facebook algorithm deciding what you see.

There’s lots more I could advise doing, but if you’re only using Facebook for reading content you want to get out of Facebook, then lock the whole thing down as best as you can (privacywise) and then use https://facebook-atom.appspot.com/ to suck the data you want out as a feed and pipe it into a feed reader.

You can unsubscribe or unfollow folks to limit your feeds to the bare minimum. The atom feed the appspot tool gives you will be everything and it will be reverse chronological. Good feed readers like Feed.ly and Inoreader will allow you to filter out posts you don’t want to see using a variety of keyword filters.

If you need specific help in setting it up or the instructions are unclear, let me know; I’m happy to help.

If you want to set up and run your own custom private system/server for close family, I can make some suggestions for doing that too.

Reposted Aaron Parecki on Twitter (Twitter)
It never occurred to me that people would be blaming @oauth_2 for the Facebook mess. Friendly reminder that OAuth is what lets you control *which* parts of your Facebook data apps get access to, and what lets you revoke that access, which you can do here: https://www.facebook.com/settings?tab=applications
Quoted Slack chat by Chris BeckstromChris Beckstrom (chat.indieweb.org)
...holy crap this stuff [IndieWeb] is great. When I started getting webmentions from social media using Bridgy I flipped. It's like we're in the future!!!
I remember the early days of Twitter when people were excited about what it was and what it could do. Even then I don’t think people were as excited as Chris Beckstrom was when he made what is certainly the IndieWeb quote of the week this morning.
Following much of the recent Facebook privacy and data scandal over the past several days, 1–4 today I deleted 169 of 184 apps which had access to all or parts of my Facebook data. Often many of them also had access to data by proxy of my family, friends, and acquaintances.

Of those apps still remaining, 7 are apps that I’ve made personally, and the remainder solely help me export data from Facebook. Short of quitting the platform altogether, this feels like a good first step to limiting the data that I leak into the platform and their partners.

For several years now I’ve been posting content to my own personal website first and syndicating it to Facebook secondarily. Few, if any, of these old apps need any legitimate access to my account anymore presuming that they ever really did.

Want to do an audit of your own app access and make a similar purge? The IndieWeb community has some resources for doing so quickly. Looking for a better place to own and better control your own data? They can help there too.

References

1.
Graham-Harrison E, Cadwalladr C. Revealed: 50 million Facebook profiles harvested for Cambridge Analytica in major data breach. the Guardian. https://www.theguardian.com/news/2018/mar/17/cambridge-analytica-facebook-influence-us-election. Published March 17, 2018. Accessed March 20, 2018.
2.
Rosenberg, M, Confessore N, Cadwalladr C. How Trump Consultants Exploited the Facebook Data of Millions. The New York Times. https://www.nytimes.com/2018/03/17/us/politics/cambridge-analytica-trump-campaign.html. Published March 17, 2018. Accessed March 20, 2018.
3.
Grewal P. Suspending Cambridge Analytica and SCL Group from Facebook | Facebook Newsroom. Facebook Newsroom. https://newsroom.fb.com/news/2018/03/suspending-cambridge-analytica/. Published March 16, 2018. Accessed March 20, 2018.
4.
Madrigal AC. What Took Facebook So Long? The Atlantic. https://www.theatlantic.com/technology/archive/2018/03/facebook-cambridge-analytica/555866/. Published March 10, 2016. Accessed March 20, 2018.

Following Casey Fiesler

Followed Casey Fiesler (Casey Fiesler)
#academia #internet #law #feminism #geek Casey Fiesler is an assistant professor in the Department of Information Science (and Computer Science, by courtesy) at the University of Colorado Boulder. Armed with a PhD in Human-Centered Computing from Georgia Tech and a JD from Vanderbilt Law School, she primarily researches social computing, law, ethics, and fan communities (occasionally all at the same time).
An interesting researcher at the intersections of law, online communities, and social media.

👓 Suspending Cambridge Analytica and SCL Group from Facebook | Facebook Newsroom

This is sure to cause a privacy firestorm. Or make the already growing one worse.

👓 One more reason not to sweat the robot takeover | Doc Searls

Read One more reason not to sweat the robot takeover by Doc Searls (doc.blog)
Long ago a high school friend wanted to connect through Classmates.com. We fell out of touch, but Classmates did not. It kept spamming me with stuff about my long-dead high school until I got it, somehow, to stop. Now I just got a mail from Classmates.com tempting me to know more about a classmate of mine from "Calabasas Academy Calabasas, CA Attended ’95-’99." Classmates' marketing robot calls me Jim and has a mailbox for me (see the image to the right) containing three promotional emails from itself. My high school was at the other end of the country, and I graduated in 1965.

🔖 A Twitter bot to find the most interesting bioRxiv preprints | Gigabase or gigabyte

Bookmarked A Twitter bot to find the most interesting bioRxiv preprints (Gigabase or gigabyte)
TLDR: I wrote a Twitter bot to tweet the most interesting bioRxiv preprints. Follow it to stay up to date about the most recent preprints which received a lot of attention. The past few months have…
h/t to

🔖 [1803.03443] Fake news propagate differently from real news even at early stages of spreading

Bookmarked Fake news propagate differently from real news even at early stages of spreading by Zilong Zhao, Jichang Zhao, Yukie Sano, Orr Levy, Hideki Takayasu, Misako Takayasu, Daqing Li, Shlomo Havlin (arxiv.org)
Social media can be a double-edged sword for modern communications, either a convenient channel exchanging ideas or an unexpected conduit circulating fake news through a large population. Existing studies of fake news focus on efforts on theoretical modelling of propagation or identification methods based on black-box machine learning, neglecting the possibility of identifying fake news using only structural features of propagation of fake news compared to those of real news and in particular the ability to identify fake news at early stages of propagation. Here we track large databases of fake news and real news in both, Twitter in Japan and its counterpart Weibo in China, and accumulate their complete traces of re-posting. It is consistently revealed in both media that fake news spreads distinctively, even at early stages of spreading, in a structure that resembles multiple broadcasters, while real news circulates with a dominant source. A novel predictability feature emerges from this difference in their propagation networks, offering new paths of early detection of fake news in social media. Instead of commonly used features like texts or users for fake news identification, our finding demonstrates collective structural signals that could be useful for filtering out fake news at early stages of their propagation evolution.

Thoughts on linkblogs, bookmarks, reads, likes, favorites, follows, and related links

Within the social media space there’s a huge number of services that provide a variety of what I would call bookmark-type functionality of one sort or another. They go under a variety of monikers including bookmarks, likes, favorites, stars, reads, follows, claps, and surely many quirky others. Each platform has created its own semantics which don’t always overlap with the others.

Because I’m attempting to own all of my own data, I’ve roughly mapped many of these intents into my own website. But because I have the ultimate control over them, I get to form my own personal definitions. I also have a lot more control over them in addition to adding other metadata to each for better after-the-fact search and use within my personal online commonplace book. As such, I thought it might be useful to lay out some definitions (both for myself and others) for how I view these on my website.

At the basest level, I look at most of these interactions simply as URL permalinks to interesting content and their aggregation as a “linkblog”, or a feed of interesting links I’ve come across. The specific names given to them imply a level of specificity about what I think exactly makes them interesting.

In addition to a bookmark specific feed, which by itself could be considered a “traditional” linkblog, my site also has separate aggregated feeds for things I’ve liked, read, followed, and favorited. It’s the semantic reasons for saving or featuring these pieces of content which ultimately determine which names they ultimately have. (For those interested in subscribing to one or or more, or all of these, one can add /feed/ to the ends of the specific types’ URLs, which I’ve linked,  for an RSS feed. Thus, for example, http://boffosocko.com/type/link/feed/ will give you the RSS feed for the “Master” linkblog that includes all the bookmarks, likes, reads, follows, and favorites.)

On my site, I try to provide a title for the content and some type of synopsis of what the content is about. These help to provide some context to others seeing them as well as a small reminder to me of what they were about. When appropriate/feasible, I’ll try to include an image for similar reasons. I’ll also often add a line of text or two as a commentary or supplement to my thoughts on the piece. Finally, I add an icon to help to quickly visually indicate which of the types of posts each is, so they can be more readily distinguished when seen in aggregate.

In relative order of decreasing importance or value to me I would put them in roughly the following order of importance (with their attached meanings as I view them on my site):

  1. Favorite – This is often something which might easily have had designations of bookmark, like, and/or read, or even multiple of them at the same time. In any case they’re often things which I personally find important or valuable in the long term. There are far less of these than any of the other types of linkblog-like posts.
  2. Follow – Indicating that I’m now following a person, organization, or source of future content which I deem to have enough regular constant value to my life that I want to be able to see what that source is putting out on a regular basis. Most often these sources have RSS feeds which I consume in a feed reader, but frequently they’ll appear on other social silos which I will have ported into a feed reader as well. Of late I try to be much more selective in what I’m following and why. I also categorize sources based on topics of value to me. Follows often include sources which I have either previously often liked or bookmarked or suspect I would like or bookmark frequently in the future. For more details see: A Following Page (aka some significant updates to my Blogroll) and the actual Following page.
  3. Read – These are linkblog-like posts which I found interesting enough for one reason or another to have actually spent the time to read in their entirety. For things I wish to highlight or found most interesting, I’ll often add additional thought or commentary in conjunction with the post.
  4. Like – Depending on the content, these posts may not always have been read in their entirety, but I found them more interesting than the majority of content which I’ve come across. Most often these posts serve to show my appreciation for the original source of the related post as a means of saying “congratulations”, “kudos”, “good job”, or in cases of more personal level content “I appreciate this”, “you’re awesome”, or simply as the tag says “I liked this.”
  5. Bookmark – Content which I find interesting, but might not necessarily have the time to deal with at present. Often I’ll wish to circle back to the content at some future point and engage with at a deeper level. Bookmarking it prevents me from losing track of it altogether. I may optionally add a note about how the content came to my attention to be able to better remember it at a future time. While there are often things here which others might have “liked” or “favorited” on other social silos, on my site these things have been found interesting enough to have been bookmarked, but I haven’t personally read into them enough yet to form any specific opinion about them beyond their general interest to me or potentially followers interested in various category tags I use. I feel like this is the lowest level of interaction, and one in which I see others often like, favorite, or even repost on other social networks without having actually read anything other than the headline, if they’ve even bothered to do that. In my case, however, I more often than not actually come back to the content while others on social media rarely, if ever, do.

While occasionally some individual specimens of each might “outrank” others in the category above this is roughly the order of how I perceive them. Within this hierarchy, I do have some reservations about including the “follow” category, which in some sense I feel stands apart from the continuum represented by the others. Still it fits into the broader category of a thing with a URL, title, and high interest to me. Perhaps the difference is that it represents a store of future potentially useful information that hasn’t been created or consumed yet? An unseen anti-library of people instead of books in some sense of the word.

I might also include the Reply post type toward the top of the list, but for some time I’ve been categorizing these as “statuses” or “note-like” content rather than as “links”. These obviously have a high priority if lumped in as I’ve not only read and appreciated the underlying content, but I’ve spent the time and thought to provide a reasoned reply, particularly in cases where the reply has taken some time to compose. I suppose I might more likely include these as linkblog content if I didn’t prefer readers to value them more highly than if they showed up in those feeds. In some sense, I value the replies closer on par to my longer articles for the value of not only my response, but for that of the original posts themselves.

In general, if I take the time to add additional commentary, notes, highlights, or other marginalia, then the content obviously resonated with me much more than those which stand as simple links with titles and descriptions.

Perhaps in the near future, I’ll write about how I view these types on individual social media platforms. Often I don’t post likes/favorites from social platforms to my site as they often have less meaning to me directly and likely even less meaning to my audiences here. I suppose I could aggregate them here on my site privately, but I have many similar questions and issues that Peter Molnar brings up in his article Content, Bloat, privacy, arichives.

I’m curious to hear how others apply meaning to their linkblog type content especially since there’s such a broad range of meaning from so many social sites. Is there a better way to do it all? Is it subtly different on sites which don’t consider themselves (or act as) commonplace books?

👓 Most major outlets have used Russian tweets as sources for partisan opinion: study | Columbia Journalism Review

Read Most major outlets have used Russian tweets as sources for partisan opinion: study by Josephine Lukito and Chris Wells (Columbia Journalism Review)
In a new study at the University of Wisconsin-Madison, we look at how often, and in what context, Twitter accounts from the Internet Research Agency—a St. Petersburg-based organization directed by individuals with close ties to Vladimir Putin, and subject to Mueller’s scrutiny—successfully made their way from social media into respected journalistic media. We searched the content of 33 major American news outlets for references to the 100 most-retweeted accounts among those Twitter identified as controlled by the IRA, from the beginning of 2015 through September 2017. We found at least one tweet from an IRA account embedded in 32 of the 33 outlets—a total of 116 articles—including in articles published by institutions with longstanding reputations, like The Washington Post, NPR, and the Detroit Free Press, as well as in more recent, digitally native outlets such as BuzzFeed, Salon, and Mic (the outlet without IRA-linked tweets was Vice).
How are outlets publishing generic tweets without verifying the users actually exist? This opens up a new type of journalistic fraud in which a writer could keep an army of bots and feed out material that they could then self-quote for their own needs without a story really existing.