How Facebook's News Feed Failed Me (And My Family)

As more and more people are turning to social networks to share their information, practically all of us are connecting to an ever-increasing number of people, and for the most part, we are updating more frequently, and sharing content from different sources in multiple places. The resulting increase in velocity, often termed noise, has led to practically all tools to try and assist us to find the "most relevant" data, or the "best" information, based either on activity from others in our social graph, or through our own past activity. Sometimes, this works very well, helping to make signal out of the noise. And on other occasions, it can dramatically miss the stated goal, and actually make things worse. This week, Facebook's latest enhancements appear to have had a serious negative impact on me (and my family).

As you likely already know, Facebook has been working on a slew of changes to its "news feed", the main column on the site that alerts you to friends' activity. The social network implemented "real time" updates to show you when new entries were posted, and very recently divided the feed into two parts - a "Live Feed" for all updates as they occurred, with the newest on top, and a "News Feed", ostensibly from those who I engage with most often, or for "hot" content - presumably measured through interaction. This is a similar approach taken to FriendFeed's "best of day", PostRank's work on RSS feeds, and Google Reader's new feature, "Magic".

This weekend was a busy one for me, one where I was less connected to the computer than usual. As a result, I checked in to Facebook only a handful of times. Glancing at the News Feed on Saturday, nothing particularly stood out. The same held true on Sunday. I was greeted with updates from friends like Jason Goldberg and Chris Saad, both solid tech entrepreneurs. I also saw notes from Robert Scoble and a handful of connections that originated on FriendFeed. Still, nothing amazing to report.



But after 11 p.m. Sunday night, I saw a friend from high school make a mundane update, saying he had a good weekend, one he would cap off with a round of "Anno 1404." Turns out that's a city-building game, like Sim City. No big deal. I clicked through to his wall to see if he hinted at the good weekend. At the top of his wall, I saw something truly interesting. A simple update, his wall said, "Don likes Malinda Gray's photo." Malinda is my 23-year-old sister. Why would he be looking at her photos? And what photo?

I clicked through, and to my surprise found out that my other sister, 28, had given birth to a new baby boy, her first, making me an uncle. Wow! After more investigation, I found that my sister, as well as my mom, and also the mother of the child, had made posts on Facebook throughout the day Sunday on the progress of the labor, and how things had gone. I also found out that my sister had actually gone into labor and started that process around noon on Saturday - the previous day, and that I had absolutely no clue.

How could I have missed it, considering they had been updating Facebook regularly, and amassing a good share of comments and likes with each update? Well, apparently, Facebook didn't figure out that this update stream was relevant to me. It didn't realize and start sending - with alarm bells - that Louis's sister was having a baby. It didn't realize that photos from my sister, both of them, of a new baby, and the hospital just prior, were more important, than a random "OH" via Twitter from Chris.

Facebook's filter failed me. While, yes, I could have clicked on each of my individual family members' profiles at any point over the prior 24 hours, or yes, I should maybe make a Family-only list and make sure to visit it regularly, I've so far trusted the network to do a good job at gauging relevancy. Yes, it's true that I interact more often with Jason Goldberg or Johnny Worthington on Facebook than I do with my own family, but in this case, the News Feed hid the only truly relevant thing that was going on this weekend, and we missed it.

I explain further in the below video:

Cadmus Filters Real Time Streams to Reduce Clutter

The more people and blogs you follow on social networks and through RSS, the more likely it is that you are going to see duplicate data, be it via retweets, forwards, or through many of your friends sending the latest viral videos or images. A new product under development, called Cadmus, looks to filter your real time streams to group similar posts in your feeds to reduce the noise. The service currently works on your Twitter account, your FriendFeed account, or on any number of blogs you add. You can also add many RSS feeds at once via OPML.


Adding Supported Services to Cadmus
In my testing of Cadmus, I found it correctly detected retweets, replies from others to the original sender, copies of tweets sent to FriendFeed, and other topically-related items, even if they did not share keywords. Cadmus was even able to find similar updates that were hours or days apart.


The Results: A Quieter Feed By About 10 Percent
On average, each refresh of Cadmus filtered around 10 percent of my updates. For runs that included 3,000 or so updates, 300 individual items would be grouped or filtered - and testing of a smaller account in the low hundreds also showed a similar 10 percent filter rate. In fact, the more updates I filtered, the higher the percentage filtering would be found. In a run comprising more than 8,000 items, almost 1,000 were "related".


Cadmus Knew Both Micah and Chris Were Watching a Show

Cadmus Saw Guy Talking About an Article TechCrunch Mentioned

Cadmus Linked Thomas Power's Like of Loic's Share
The authors, Anomaly Innovations, who are chronicling Cadmus' development on their blog, show even higher filtering rates, of almost 30 percent, if you looked at an entire week's worth of updates. And while most of the filtered items only had one or two related posts, you can see an extreme version from the last week here.

To use Cadmus, you need to log in at http://thecadmus.com/, using OAuth, to your Twitter account, and you can add as many supported services as you like to the system. Once you have scanned your stream, click the reload button in the top right to get a newly filtered stream. If you're tired of seeing duplicates, want a stream with less noise, or just want to lump similar items, it is an interesting development - one I expect to get better as they continue to update.

Parse.ly Spices Up the News Based On Your Interest Filters

I am enjoying seeing the growth in Web services tailored to finding the very best news just for me. From My6Sense's attempt to only show me the best news, and hiding the less-important items, to Lazyfeed's topics-based blog search engine, we've recently seen two interesting approaches to cutting through information overload and finding the best data. A new invite-only beta service, called Parse.ly, claims to offer "fresh content" with "minimal garnish", and, leveraging my interests, gives me the highest-ranked stories, derived not just from my leanings, but how strongly I find myself aligned with specific topics. The result is another news source with an outstanding signal to noise ratio.

If you are among the lucky few who has thus far obtained access to Philadelphia-based Parse.ly (I am betting the best way is to follow their Twitter account), you start by entering terms you want to find news on, and dragging them to boxes that signify your intensity of interest. The five boxes range from "Most" to "Extremely", "Very", "Moderately" and "Somewhat", in descending order.


Prioritizing My News In Parse.ly
Per my usual approach, I filled the boxes with tech terms, and deigned to see if Parse.ly could find me new, interesting stories about the topics I am most interested in. And it came through - no question.

Each of the buckets ("Somewhat" to "Most") gained a numerical score, from 2 to 10. As a result if a blog post had two of my "10 point words" in its title or excerpt, it would have 20 points, and be pushed to the top of the results queue. Higher yet would be a story on Google around Pubsubhubbub and RSS, which weighed in at 28 points, sporting two 10 point words and an 8 pointer. Like traditional feed readers, Parse.ly shows the title of the story and the date, but it also includes a short summary and, yes, the post's numerical score. Sorting by score shows the highest ranking results.


My Starred Items In A Parse.ly Reading Pane

How Stories Got Scored Based On My Preferences
If you click on a story in the standard view, an excerpt is displayed in the reading pane, which also features a "Score Explanation". And if you click on the story itself, a new window will open with a Parse.ly share bar, prompting you to either save the story for later viewing, or share it to a myriad of other social networks.


The Parse.ly Sharebar In Action on eWeek
Parse.ly clearly states that its focus is all about the content and minimal when it comes to garnish (or design). That's absolutely the case. The product is reminiscent of GMail and Google Reader with its simple interface and the ability to star items, or show only read and unread items. You can also archive old items or delete them, just like you would for old e-mails and RSS feeds.

I am eager to see Parse.ly open up and let people get into the product, for while I have plenty of places to get news, Parse.ly has among the best I've ever seen in terms of quality. The company even says it could be a solid alternative to Google Alerts. Not a single spam blog was found, a testament to Parse.ly's selection from 50,000 different sources. The option to share out to other networks will also make it an interesting part of the social ecosystem.

Podcast: TheSocialGeeks: Stop Being Lazy, and Filter

In the latest edition of The Social Geeks, Chris Miller, Wayne Sutton, Jeff(isageek) and I talk about new introductions on Lazyfeed, Google Reader, and how to interact with multiple communities on differing social networks. Meanwhile, have we reached the saturation point where we no longer have to look for more sources of news? I say no, but stress that filters can play a big role in getting the best data. You can also find the original copy on Mevio.com.

Personalize Your Feeds With Feedweaver

By Corvida Raven of SheGeeks.net (FriendFeed/Twitter)

As RSS makes attempts at going mainstream, pioneering services such as Yahoo! Pipes, Toluu, ReadBurner, and RSSMeme are helping the process of expanding applications' possibilities with RSS. Now, you can add Feedweaver to that list.

One thing I've always looked forward to in the space of RSS is the ability to share personalized groups' feeds. I can't wait to see the day when we all will share groups of personalized feed recommendations with friends and family. The digital age would really be in effect for me if this were to happen. So imagine my delight when I ran across Feedweaver, a web feed aggregator that helps you personalize your feeds.

Simply put, you're able to turn a group of individual feeds into one feed for sharing purposes.

What will immediately catch your eye with Feedweaver is the site's design. This is one gorgeous site to look at. The simplicity of the site's design led me to feel like there wouldn't be a learning curve for using this site, something mainstream users often struggle with.

Creating a feed is simple, but also has the potential to be taxing. Once you give your personalized feed a name, you need to start adding URLs, and this is where you have your work cut out for you. On the Web, there is really no easy or automatic solution to adding feeds unless you have an OPML file. Unfortunately, Feedweaver doesn't offer OPML file support on the site, leaving you the arduous task of typing in every RSS link one by one.

Some of you may subscribe to hundreds of feeds. I do. If you were to create a personalized feed, how many blogs would you probably add? 10? 20? 50? 100?

Leave a comment saying "I definitely don't suffer from ADD," if you're happily willing to find and type in 20 to 40 RSS feed links to create one feed. It would even be easier if you didn't need to type in the exact feed link. Why not make it easier and let users type in site links too and have Feedweaver find the exact RSS feed link for us?

Feedweaver adds filtering into the mix by allowing the users to create keyword filters for each feed link that you list. When you're done, grab the url given by Feedweaver to share with friends and colleagues. Feedweaver allows you to come back and manage your group feeds without any fuss. If you have a few feeds that you'd like to send company employees or to groups of friends, Feedweaver would be a good service to use. All in all, it's an easy to use aggregator for anyone that's not dealing with information overload.

Read more by Corvida Raven at SheGeeks.net.

Feedscrub: Cleanse The Dirt From Your RSS Feeds

By Mike Fruchter of MichaelFruchter.com (Twitter/FriendFeed)


Last week I touched upon RSS overload and how it's starting to become a problem for a lot of people. That post mainly reflected on how to get the most out of your Google Reader in terms of organization and productivity. The overload part for many, comes down to feed management. In the past I suggested unsubscribing from feeds that bring you little value, or update with too much frequency.

That eliminates the problem, but also poses the risk that you might miss something valuable mixed in with all the clutter. I recently found a better solution, which I have been testing for about 24 hours now, it's call Feedscrub.com.

What is Feedscrub?

Feedscrub is a clever filtering system for your RSS feeds. It acts as a spam filter for your RSS feeds. With this system, you train it based on your content preferences. This application now allows me to still stay subscribed to the feeds I otherwise would have unsubscribed from ages ago. I'm always weary that I will miss something of importance if I abandon the feed completely. For instance, I'm subscribed to quite a few technology blogs, so the first thing I did with Feedscrub was train it to scrub posts that have anything to do with Apple.

The training filter is like an email filter that is based off words. I'm not an Apple consumer and quite frankly I'm overwhelmed with feed after feed pertaining to Steve Job's health or the iPhone. By scrubbing the posts in my feeds that have any mention of Apple, I'm training the system with my dislikes and hopefully I will never have to see another post relating to Apple in my Google Reader.

Getting started:

Getting started with the service is pretty straight forward. You have the ability to enter up to three feeds for scrubbing. Because the service is still in beta, and they are still working out the kinks behind the scenes, three should be suffice to get you going and to take it for a test drive. My advice for you is to test the service out with your feeds that update quite often throughout the day. This will show you the power of the filtering faster compared to feeds with less frequent updates. Don't worry,for power users they offer a PRO account which gives you unlimited feeds plus OPML import & export.


After you input your selected feed for scrubbing, they are displayed and stored under the "Manage Feeds" tab in the control panel. From here, you will also see three feed reader subscribe buttons under each feed. In order to train the system, you must subscribe to the Feedscrub feeds, replacing the original one in your feed reader. Here is what the Feedscrub feed looks like. It basically adds two buttons to the feed, one called "scrub it", the other called "save it". These are what you will use to train the system. If you like the article of content on the feed, you click save it, dislike it, click scrub it. Simple enough.

Training is not limited to the Feedscrub site:

You can train the system a variety of ways. When logged into the control panel you can click the corresponding feed. That will launch a new window with the feed as outlined in the below screen shot. The save it and scrub it buttons are located on the feed. Train away!


Power users will prefer training inside the comfort of Google Reader:

If you are using Google Reader, the feeds that you have selected for scrubbing, appear with the save it, and scrub it buttons. This is how I'm currently training the system. It's handy and convenient, and what better place for them to appear than in your RSS vehicle. This makes it even easier to train the system. Once you have your selected feeds into the Feedscrub system, you will not have to be logged into the control panel often to train and filter your feeds.


That concludes part one of a two-part post:

In order for me to give a fair review of the application, 24 hours was not enough time for me to make a full assessment of the filtering system. Feedscrub was courteous enough to supply me with a PRO account for testing purposes. I unloaded some 600+ feeds into the system last night, so it was a time consuming process. Out of the 600+ feeds, I'm selecting approx 50 of them for scrubbing. One week should be ample time to train the filters, and the data set should be rather interesting. I will share the results of my findings in about a weeks time.

Take the service for a test drive. We have beta invites!

Feedscrub graciously supplied us with 150 beta invites. These will go fast. Don't hesitate to sign up. Use invite code "louisgray" at the sign up process.

Read more by Mike Fruchter at MichaelFruchter.com.

AideRSS Rebrands as PostRank, Launches New Features, API

Since its launch, AideRSS has aimed to leverage social tools to help determine a publisher's most popular content, through analysis of individual posts and their related activity, including Diggs, bookmarks on Delicious, links in Google, and total comments. RSS advocates suffering from information overload have even turned to AideRSS to act as an intelligent filter, providing them the best stream, rather than the default firehose. With today's new announcements, along with a rebranding as PostRank that saw the launch of a new Web site and look, the service has added tags, keyword filtering, and other tools that will get users to the data they are seeking quickly.

(See from December 2007: AideRSS Judges Feed Posts as Good, Great, Best)


PostRank Shows Posts With Audience Engagement Have Higher Score
The first major enhancement to the new PostRank is keyword filtering. As Ilya Grigorik wrote, users have asked for the ability to customize and filter any RSS feed with specific keywords. For example, you could get all posts from The Unofficial Apple Weblog that mention iPhone, or posts from Matt Cutts that mention SEO.


I Tagged TUAW as iPhone and Filtered for Only iPhone News
You can also now tag feeds you import into PostRank, helping to build out what the team calls "custom content channels" based on those tags and keywords. All feeds tagged with BlackBerry would be in the BlackBerry channel, etc.

Most interesting to developers may be the introduction of full API access. According to Grigorik, all operations possible on the new postrank.com site are accessible by API, making it easy to utilize the filtering capabilities seen in their service on other applications.

As a blogger, the new PostRank offers better ways to see if specific posts do better with readers and the social services based on keywords. As a consumer, you can now read fewer feed items and still be sure you don't miss those that are most interesting to you. You can find PostRank at http://www.postrank.com. Of course, going to the old AideRSS.com will push you there as well...

Filters and Belief Systems

By Rob Diana of Regular Geek (Twitter/FriendFeed)

Some days, there is a minimal amount of news and discussion. Yesterday was one of those days. Today, however, is different. In the morning, I read my feeds and had two interesting posts that will spark much discussion today.

First, Mark 'Rizzn' Hopkins has quit FriendFeed. I am disappointed, but he puts it concisely, "Unfortunately, I just don't think I can take it anymore." In Mark's case, it was a political discussion that went awry that broke the camel's back. He lists the usual problems with any internet discussion, people not doing any fact checking and just spewing opinions, people insulting your intelligence and people calling you a racist. Disappointingly, the internet is full of people with different opinions and many discussions end in this manner. He does summarize his feelings nicely though:

As I said before, it's not a blanket indictment of everyone on there, but of the community spirit on the system. Almost everyone I know uses FriendFeed, and that includes my best friends. Somehow, though, when all my friends (and their friends, and their friends) get together in a conversation, something goes horribly awry.

The second blog post came from Louis Gray where he talked about his dilemma of being a Mormon, a Democrat, a friend of gay people and how to vote on California's Proposition 8. Prop 8 is a highly divisive issue because it is about eliminating the rights of same-sex couples to marry. Louis' dilemma stems from the idea that "Politics and religion make tough bedfellows. (No pun intended)." As a Democrat, he should obviously be against Prop 8, but as a Mormon he should obviously be supporting Prop 8. So, what do you do? This dilemma is true of any liberal-minded person who is also religious, because most religions are against same-sex marriages. The problem really comes down to something Louis mentions:

In theory, politics should be based on one's studying of the issues, and reaching a conclusion through a combination of facts. Religion, while often largely fact-based, also asks you to make decisions based on faith in things not fully understood and unseen, while trusting leadership who give guidance said to be of divine source.

Of course, Louis is already wondering what kind of response this will draw on FriendFeed. So, what do these posts have in common? Politics and religion. What is the common bond between these two topics? Belief systems. As much as people want to believe Louis' assertion, politics is based on studying the issues and reaching a conclusion based on facts, most people base their politics on their religious beliefs. These types of topics are very volatile because disagreement becomes an attack on "everything we believe".

The Importance of Filters

I have talked previously about the importance of filters when using an application like FriendFeed. Filters are mostly talked about in how to find information in the flood of noise. However, filters can also be used to avoid things you do not want to listen to. Anyone who follows me on FriendFeed can find that I rarely take part in conversations about politics or religion. There is a very good reason for this. Look at any of the political discussions lately on FriendFeed. You will find that the conversations may start as intelligent but eventually degrade into name calling. This is not always true, but it happens often enough. When belief systems are involved, I tend to avoid the conversation because I want to enjoy my experience, not argue.

This is the main reason I am disappointed with Mark Hopkins' decision to leave FriendFeed. His disgust with some of the conversations is his own making. Not because of his political views, but because he partakes in the political discussion. I value the benefits of FriendFeed too highly to allow the political discussions to bother me. I hide most political items because I am not on FriendFeed for that purpose. I may find some interesting political article to read, but I not discussing things there. The main reason is because I do not want to leave FriendFeed.

With services like FriendFeed and Twitter, you really do need some method of filtering. One of the obvious methods is a FriendFeed list. For Twitter, you can use software like TweetDeck to group users. The difference is that using application filters can improve your experience. That is why they exist. The other part of the filter equation is you. You may need to filter yourself. What I mean is that if you really like something, there may be compromises that need to be made. In Mark's case, maybe this means not getting involved in as many political discussions. If you do not like what Louis said in his recent post, then just hide the post.

The most important ingredient in the filters is you. If you do not like what is being said, you do not have to listen.

Read more by Rob Diana at RegularGeek.com.