PolitEcho shows you the political biases of your Facebook friends and news feed. The app assigns each of your friends a score based on our prediction of their political leanings then displays a graph of your friend list. Then it calculates the political bias in the content of your news feed and compares it with the bias of your friends list to highlight possible differences between the two.
The Washington Post recently published an article about social media metrics with an alarmist headline: 6 in 10 of you will share this link without reading it, a new, depressing study says This story then predictably made the rounds in the blogosphere, from Gizmodo to Marketing Dive. The headline reads like self-referential clickbait, daring readers to click on the provocative …
Fake news is the easiest of the problems to fix.
…a new set of ways to report and share news could arise: a social network where the sources of articles were highlighted rather than the users sharing them. A platform that makes it easier to read a full story than to share one unread. A news feed that provides alternative sources and analysis beneath every shared article.
This sounds like the kind of platforms I’d like to have. Reminiscent of some of the discussion at the beginning of This Week in Google: episode 379 Ixnay on the Eet-tway.
I suspect that some of the recent coverage of “fake news” and how it’s being shared on social media has prompted me to begin using Reading.am, a bookmarking-esqe service that commands that users to:
Share what you’re reading. Not what you like. Not what you find interesting. Just what you’re reading.
Naturally, in IndieWeb fashion, I’m also posting these read articles to my site. While bookmarks are things that I would implicitly like to read in the near future (rather than “Christmas ornaments” I want to impress people with on my “social media Christmas tree”), there’s a big difference between them and things that I’ve actually read through and thought about.
I always feel like many of my family, friends, and the general public click “like” or “share” on articles in social media without actually having read them from top to bottom. Research would generally suggest that I’m not wrong.   Some argue that the research needs to be more subtle too.  I generally refuse to participate in this type of behavior if I can avoid it.
Some portion of what I physically read isn’t shared, but at least those things marked as “read” here on my site are things that I’ve actually gone through the trouble to read from start to finish. When I can, I try to post a few highlights I found interesting along with any notes/marginalia (lately I’m loving the service Hypothes.is for doing this) on the piece to give some indication of its interest. I’ll also often try to post some of my thoughts on it, as I’m doing here.
Gauging Intent of Social Signals
I feel compelled to mention here that on some platforms like Twitter, that I don’t generally use the “like” functionality there to indicate that I’ve actually liked a tweet itself or any content that’s linked to in it. In fact, I’ve often not read anything related to the tweet but the simple headline presented in the tweet itself.
The majority of the time I’m liking/favoriting something on Twitter, it’s because I’m using an IFTTT.com applet which takes the tweets I “like” and saves them to my Pocket account where I come back to them later to read. It’s not the case that I actually read everything in my pocket queue, but those that I do read will generally appear on my site.
There are however, some extreme cases in which pieces of content are a bit beyond the pale for indicating a like on, and in those cases I won’t do so, but will manually add them to my reading queue. For some this may create some grey area about my intent when viewing things like my Twitter likes. Generally I’d recommend people view that feed as a generic linkblog of sorts. On Twitter, I far more preferred the nebulous star indicator over the current heart for indicating how I used and continue to use that bit of functionality.
I’ll also mention that I sometimes use the like/favorite functionality on some platforms to indicate to respondents that I’ve seen their post/reply. This type of usage could also be viewed as a digital “Thank You”, “hello”, or even “read receipt” of sorts since I know that the “like” intent is pushed into their notifications feed. I suspect that most recipients receive these intents as I intend them though the Twitter platform isn’t designed for this specifically.
I wish that there was a better way for platforms and their readers to better know exactly what the intent of the users’ was rather than trying to intuit them. It would be great if Twitter had the ability to allow users multiple options under each tweet to better indicate whether their intent was to bookmark, like, or favorite it, or to indicate that they actually read/watched the content on the other end of the link in the tweet.
In true IndieWeb fashion, because I can put these posts on my own site, I can directly control not only what I post, but I can be far more clear about why I’m posting it and give a better idea about what it means to me. I can also provide footnotes to allow readers to better see my underlying sources and judge for themselves their authenticity and actual gravitas. As a result, hopefully you’ll find no fake news here.
Of course some of the ensuing question is: “How does one scale this type of behaviour up?”
During the election, many people fell prey to fake news stories on social media -- even the president-elect ended up retweeting fake statistics. A professor of communication has created a list of unreliable news sites to help people do better.