Klout, Triberr, paper.li, and the future of content curation

Klout for content filteringWe are all facing huge information overload these days. There is so much available content on just about any subject that separating the wheat from the chaff is becoming increasingly difficult. Therefore, content curation is now more important than ever.

A number of new services have surfaced to meet these challenges. In this post, I will examine the solutions they provide and the implications of these solutions.

Content curation is the searching, selecting, and sharing of valuable content on a specific subject. Selection has traditionally been done by humans, and indeed, some definitions of content curation specify that it should be done by humans, but in practice it is more and more often done by machines. I think automated curation is a sound idea; it is plausible the computers can curate instead of merely aggregate, although the success of its implementation remains to be seen.

I will attempt to categorize the various curation solutions with examples of each category, after which I will evaluate what all of this means.

Tools for an individual content curator (scoop.it)

Scoop.it is a content curation service that comes with content discovery tools that can aid you in finding quality content, after which you can manually share it in your topic, which is essentially a topic-based content repository.

Scoop.it is traditional content curation aided by new technology: the curator makes all the choices and can bring in material from anywhere, but the configurable discovery tools help find material and allow sharing it easily.

It is the evolution of content curation as we know it, but the big question is whether this is enough: as the amount of available content increases, it will be increasingly difficult to keep up with the information flow.

Crowdsourced content curation (Digg and Stumbleupon)

One way to answer the information overflow is to get lots of people to curate it collectively. Digg and StumbleUpon are social bookmarking sites, which effectively act as crowdsourced content curation engines.

There are differences in the implementation, as Digg tends to drive a whole lot of traffic to the most popular content whereas StumbleUpon is based on a degree of randomness that exposes less obvious content to more users and uses the results of this random discovery to promote popular content to an increasing number of users.

To an extent, crowdsourcing works, and according to some reports StumbleUpon distributes a significant amount of traffic (see the story here).

Crowdsourcing works best when there is a sufficient number of people interested in the subject. For more niche subjects, it is not able to provide results. Then again, niche subjects should have less content in the first place, so merely being able to find it might allow an individual curator to perform adequately.

Automated or semi-automated content curation (paper.li)

Paper.li is an automated content curation service. You set up search criteria, such as keywords, Twitter lists, Twitter users, or RSS feeds, and the service creates a daily newspaper for you from the links it picks up from them and can even use your account to tweet to promote it.

After setting up the search criteria, all the rest is done automatically. The paper is published as configured with no interaction whatsoever.

The newspaper format employed by paper.li is comfortable for people to read. We are used to it, it is familiar, and this makes it attractive. However, it can also be misleading: if the content is based on certain keywords and there is no editorial work involved, is it really content curation at all? I would say that it is not, as it lacks selectivity!

Paper.li has recognized this, and has constantly introduced more editorial features: you are able to filter content based on both user and keyword (only content on certain topic from certain users appears), block content from certain users in the search criteria, as well as remove articles or rearrange them after the paper has been published. A preview mode has also been promised, so at some point you will be able to tweak your paper to your liking before publishing it.

With these advanced features, paper.li can be used as a semi-automated content curation platform: it provides you with a newspaper automatically, and you can then easily tweak it to your liking. This is semi-automated content curation: you don’t manually seek out content, instead you set the basic criteria, weed out the chaff, and arrange the rest in order of importance.

Paper.li can also be used as an automated content curation platform in one sense: you curate the people, and optionally the topics, manually, and paper.li aggregates all the content automatically. Once you have set up the people and the topics you want to follow, the service can run in full automatic mode.

Is curating people somehow better than aggregating content based on keywords? I would argue that it is. Keyword-based aggregation can be gamed, just think of all the search engine optimization in the past years, especially the black-hat variety. People-based aggregation does not provide such opportunities, as you need to pass the vetting process before being released to the stream.

Let’s examine a service that is fully based on the idea of people curation.

Manually curate people, not content (Triberr)

Triberr‘s slogan is “The reach multiplier!”, but at its core it is a content curation service. The users form tribes, and every time anyone in a tribe publishes a new post, everyone in the tribe tweets it to their followers (scheduled, not simultaneous). Nowadays, it is also possible to manually approve each tweet, so Triberr can actually also be used as a traditional content curation service instead of an automated one.

In automated use, Triberr moves the curation away from individual content into curating the people you want to be in a tribe with. In manual use, it filters content based on the content creator, and allows you to manually curate this set of content for sharing in Twitter (and probably with other social networking sites in the future).

Triberr lacks one feature that paper.li has: the ability to automatically curate content based on both the content creator and the topic. This means that unless all tribe members share very similar content, the added value from curation is diminished, because all content does not match the interests of the curator or his audience.

Automated content curation based on manual people curation (tribe members) has great potential, when the members constantly post closely aligned content. The more diverse the tribe, the more noise is introduced into the stream.

Automatically filter people (Klout)

Klout is a service that assigns everyone an influence score on a scale of 1-100 based on their activities and the actions those activities prompt from others on various social networks.

However, Klout is actually used as a filter. Several applications display the Klout scores of people: for example, in the popular Twitter application Hootsuite, you can filter your stream based on the Klout scores of people you are following. Klout scores are also used as a basis for following people on Twitter, inviting speakers to seminars, and even hiring people (for examples, read this).

What does this have to do with content curation? Klout is not a content curation tool per se, because it is not a sharing solution. However, it is a tool for searching and selecting people and content based on the content creator. Whereas in paper.li or Triberr you need to know who you are looking for, Klout rates people you do not know and allows you to filter out content from people below a configurable notability threshold. All of this is part of the same evolution process.

The future trends of content curation

There are three major trends in content curation:

  • From individual content curators to crowdsourced content curation: Individuals cannot keep up with the pace of new content, even though they have better discovery tools than before. Crowdsourcing can, although it is not suitable for promoting radical new ideas: the dictatorship of the masses is unavoidably conservative.
  • From manual to semi-automated content curation: Individual content curators are forced to automate as much of the process as possible in order to stay relevant.
  • From content curation to people curation: When there is too much content, you vet the content creators, manually or automatically. Those who pass get exposure for all of their content.

How do these trends interact? Social networking of the content creator is vitally important in order to create an audience as isolated content becomes increasingly difficult to discover and curation focuses on people instead of individual content. Build it, and they will come, is dead.

The risk: automation increases noise

Automated content curation is not yet an option. This is clearly visible in the changes paper.li and Triberr have been forced to make to their services. Both started out as mostly automated services, but popular demand has forced them to introduce more editorial features. This is good! They are on their way to become very useful semi-automated content curation services.

The risk, however, lies in the fact that the automated features are not gone. They never will be, because if paper.li and Triberr removed them, some other service would arise to take their place.

There is a major risk that these automated features will increase the amount of noise in social networks and diminish the value of these services, because it is difficult to assess whether content from these services is automated noise or valuable, manually vetted content. This difficulty is exacerbated by the fact that this noise makes the noise-makers seem more valuable for automated people filters (Klout)! Here is an example of how much Triberr can affect your Klout score (note: he is not a noise-maker).

How making noise works in practice:

  • Triberr: Form a large tribe, have everyone tweet automatically. Lots of tweets, lots of mentions = content seems valuable.
  • Paper.li: Publish automatically based on many keywords. Mention people in tweets that promote your newspaper. Some will retweet and follow you. Retweets and followers = content seems valuable.

Because automated content curation is as of yet unable to provide reasonable results, but using it provides highly increased exposure, it is the tool of spammers of the future.

This raises some serious questions for Klout as well: should Klout take mentions from Triberr into account at all? How could Klout prevent gaming the system through automated use of paper.li?

Final remarks

The very services that strive to save us from information overflow run the risk of making things worse if they are used malevolently.

At the same time, they may become mandatory for all content creators who want to create content for an audience, because it may become nigh impossible to be discovered without using them.

All of this ensures that the amount of information in the streams will keep increasing. Whether it will be signal or noise, remains to be seen.

Author: Ville Kilkku

I run my own consultancy business, so if you find the ideas on this blog intriguing, contact me at consulting@kilkku.com or call me at +358 50 588 5043 and we can discuss how I can help you solve your business problems. I am currently based in Tornio, Finland, but work globally. Google+

  • Generally speaking, I do like the way you approach problems and questions.

    But you’re thinking the wrong way about one thing. You initial reaction, however, is understandable. Even Dino leaned your way in the beginning. But he’s since come over closer to my way of thinking. Hopefully, you will too. [grin]

    Regarding triberr, you write:

    “… the added value from curation is diminished, because all content does not match the interests of the curator or his audience.”

    Curation is only diminished by the tunnel vision created by an emphasis on aligning content with the often misguided perception of an audience’s preferences. The hype that niche is king is so two years ago. It’s an industry and academic magazine model that proved a poor business model in print.

    Curate people!

    Curate people that bring passionate contribution, insight, and vision (CIV) across a variety of topics to your moveable feasts (aka timeline). Because the emphasis on niche (content) has become oh so much echo, remix, and reverb. Because quality writers and bloggers have interesting things to say to you or me – whatever they are talking about.

    Quite a few Triberr people had a problem with my way of thinking just a few months ago. Because they felt that they had to control the message. Because they felt an exaggerated responsibility to filter the noise. But some have seen the light. [grin]

    The noise is filtered not by censoring intelligent, passionate, or interesting voices that don’t fit your niche or narrow interests. The noise is filtered best by filtering out the people that have nothing to contribute on anything.

    You may also find (like I found), my audience increased as I enriched my stream with passionate, new voices.

    Or, maybe, I am mistaken…

    Join me in my latest conversation:
    Empty-handed and Less Traveled Roads. And other social media DOHs. http://wp.me/pbg0R-on

    • I can’t quite agree that sharing all material from any and all interesting people is useful.

      If there was a really small amount of good content and a whole lot of junk, then maybe that would be the case. Promoting 10 top content creators? No problem. However, the reality is that there is a lot of good content and a lot of junk, and this is where things become more difficult.

      Let’s say people universally adopted this way of thinking, and let’s say 10,000 top minds from all sorts of fields began cross-promoting each other. Then it would not matter which ones of these I follow, they would all give me the full package. Now, one day I would like to know what is going on in social media marketing. Unfortunately, because all social media marketing news are posted alongside technology news, manufacturing news, and cooking recipes, finding them is really, really hard. All the content I find is first-class, but I have a hard time finding the thing I’m interested in right now.

      On the other hand, if I could set up my curation software based on both people and topic (not an easy task, as identifying which content belongs to a fairly large field is not self-evident), I could post ideas on social media from those 10,000 top thinkers, and people would know that I am the curator to seek out for social media news.

      Triberr was created for a small group of like-minded individuals. That works. However, they recognized issues with large tribes early on and limited tribe size accordingly. This prevents the 10,000 people tribe scenario in this particular tool at the moment. But where do you draw the line? At 150? Unless there is a way to curate based on both the creator and the topic, creator-based curation is either limited to small groups, or it becomes meaningless.

      • Ville,
        I like some of the thoughts you presented in terms of content curating. As you can imagine, I am much more concerned with how Triberr plans on approach the topic.

        First, we did start out as 100% auto. It was ALL about trust and curating the right people. We now have manual mode which gives user a bit more control over what is shared.

        To help people prioritize what they should review first, we’ve introduced a social signal called Karma into the mix. Karma lets you vote up and down posts you like/dislike, sort of Digg style, but within a tribe.

        Last week we introduced the notion of a “quality score”. Quality score is measured by the click through rate of a tribemates followers in regard to your post. So if a tribemates tweets my post to his 100 followers and 5 click on the link, I’ll have a 5% click through rate. There are also other factors that play into quality score, but the major on is CTR.

        We’d like quality score to evolve in a number of ways. From factoring in on-site factors like the number of comments the post gets and the time on site to expanding it to Facebook and other social platforms.

        We really feel that by evolving quality score, karma feedback and manual controls such as negative keywords we can really put a lot of intelligence behind automated content curating.

        Give us another 6 months, and I think you’ll be quite impressed with how Triberr is leading the industry in this regard.

        • Dan, thank you for your comments.

          I took my time to reply because I wanted to read all the discussions about quality scores on Triberr blog first (such as http://triberr.com/bonfire/thread/?pg=3&thread=3971).

          The picture that I have in my mind about the issue based on your comment here and the discussions there is two-fold:

          First thought:

          You are striving to create an automated content curation engine with Karma and quality scores, and I admire this goal.

          However, there are many among your user base who are enticed by the “Reach multiplier” and not by content curation at all. This is evident in comments that oppose quality scores based on diminishing audiences, and in comments that expect you to come up with creative solutions on how to “trick” anyone who tries to avoid Triberr content (such as buying a large number of domains and using them to tweet the posts).

          I am not sure that it is possible to please both crowds. I would be extremely intrigued to hear your views on how that can be done.

          Basically, if you go for reach multiplying, many people start or continue to try to avoid Triberr content and you will constantly need to come up with new tricks to get past them. This will hurt everyone who tries to use Triberr as a content curation tool and not just an advertising tool.

          If you go for content curation, you will lose customers who want to use Triberr as an advertising tool. This is also a potentially dangerous route, because advertisers are willing to pay if the ROI is right, whereas content curators are less inclined to pay for services!

          If you try to work both ways, you will face both types of problems! The advertising crowd may be kept if all curation functions are optional, but the curators will be in trouble if Triberr becomes known as an advertising platform. I would indeed love to know your thoughts on this fundamental problem.

          Second thought:

          Karma, quality scores, and negative keywords cannot solve issues with tribes that encompass a variety of interests, and do not help make large tribes viable.

          However, they might be significant tools for encouraging people to optimize their tribes around a clear theme and place soft limits, instead of hard limits, on tribe size. This is an interesting avenue for promoting content curation, but also likely to alienate more advertisement-minded users.

          Let’s examine the features in a bit more detail:


          Karma is a useful concept for sorting out the best content from a group of similar content. However, it does not work when comparing apples and oranges. So, I’m interested in social media and documentation. If someone else in my tribe is interested in social media and photography, the only part where Karma provides meaningful comparisons is on posts about social media.

          This either means that tribes need to be formed around common interests, or there needs to be a way to introduce topic categorization into the mix to get relevant results. Asking me to grade a post on photography would be a waste of time. Should this categorization take place within Triberr, or already on the RSS feeds to the tribe, is a significant question.

          Quality score.

          Quality score is something I am not really convinced about. Anne Thornley-Brown raised a key point in your own blog about this: CTR measures headline quality.

          I am not entirely convinced by your reply, namely, that you can lure visitors with catchy headlines for a time, but not for long. As long as there are new people to click on catchy headlines, or your content is good some of the time, the effectiveness of catchy headlines does not diminish very quickly, if at all.

          The retweet part of your argument might be part of a solution though: if the headline is not very catchy (=low CTR), but the number of people who retweet after reading is high, this ratio could be used to offset the effect of CTR alone.

          There is also another aspect of CTR that I do not like: it creates a self-strengthening cycle that promotes the popular bloggers. As every Triberr tweet mentions the writer, the ones who are already popular are likely to receive more clicks regardless of the quality of the individual post.

          CTR is fundamentally an advertising measurement concept. It promotes content with catchy headlines and renowned authors, and this goes against quality curation that should look into the content itself.

          CTR also further exacerbates the critical lack of topic categorization: if the audiences of tribemates are not homogeneous, the topic has a significant effect on the CTR – I’m much more inclined to open a link on social media than on photography.

          Some on-site factors are also a bit uncomfortable when talking about blog posts: blog posts have a much higher bounce rate than regular landing pages, because they are typically read and then closed. This also affects measuring time on site. And to take this thought process further, including these factors basically measures site design and the strength of calls to action, because they have a significant effect on these figures. They provide some indication as to the quality of the post itself, but that is not all they measure.

          Comments suffer from the same effect to an extent: What commenting system does the blog use? Is there a strong call to action to leave a comment? However, they are probably the least affected, because the comment systems have the least variety.

          Retweets per reader, number of comments per reader.. You might have something there.

          CTR, bounce rates, time on site.. When measuring these, you are also measuring ad copywriting skills, author fame, and site design. The key thing to keep in mind is that you get what you measure, and I’m not sure all of these things are the things you want to strive for.

          Negative keywords.

          Now this is a partial solution to the topic issue. I put photography in my negative keyword list, and no tweets for posts about it are sent, right? Keywords go some of the way, but they may still leave out some posts I’d like to include, and not exclude some of the posts I’d want to exclude.

          I don’t think negative keywords are an ideal solution, although they are a step in the right direction. That is, if your goal is to make large, varied tribes viable. Then again, negative keywords can also make small, varied tribes more viable, because it is easier to set up guidelines in such tribes as to the keywords that direct the tweets to the correct audiences.

          To sum this all up:

          I think Karma, quality scores (if you get the measured objects right), and negative keywords can indeed make Triberr an even better platform for automated content curation for small groups of like-minded people.

          However, they do not solve the issues with larger tribes or varied interests. Only curation that takes the topic into account can achieve this goal, if it is your goal at all.

          If you survived this wall of text, I would love to hear what you think!

          • Hi Ville,

            So, Im not as smart as you and Dan, but I am the Chief of one of the original supertribes, Anubis with 35 members in it. Now, thats not the largest tribe on Tiberr anymore, but we do come from all walks of life 🙂

            There are 35 bloggers blogging about very different topics. And while I cant argue with you or Dan point by point, I can say without any reservation that it’s working for us and it’s working for our followers.

            You seam to come from a hard stance that topics must be segregated at all cost. This is a philosophical stance with which I personally dont agree with. I crave verity and I dont believe in categories. But I realize that Im more of an exception rather than a rule 🙂

          • Dino, thank you for your comment. I’m sure you’re being too modest regarding your wits. 🙂

            Yes, I suppose we have fundamentally different stances on content curation when it comes to topics: I readily admit that promoting 35 blogs on different subjects through my account is something I would never-ever consider doing.

            To be honest, I had not considered that as a serious curation option either. Now that I think about it, I suppose you are indeed able to find audiences who appreciate this kind of approach. That’s great, good for you and them!

            However, that still does not solve what I wrote in my previous comment, namely, that the curators will be in trouble if Triberr becomes known as an advertising platform that makes people desire filtering it out.

            How to keep and enhance everything that is good about it, and your comment shows that there are more good things than I had considered, and prevent excessive noise, is the big question.

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  • Ville,

    I think that your post is pretty spot on, but we must be careful not to automate so much that we lose the essential purpose behind social media — interacting and engaging. If we rely on curation too much, then we will render social media useless. However, it is important to begin filtering out the crap, so to speak, so that people looking for valuable resources don’t get frustrated because of their inability to find relevant content.

    That said, you should check into Buffer (bufferapp.com), which is my preferred way of automating my curation. It allows me to share the things I would have shared in real time any way, putting them automatically on a schedule I choose, and then freeing up my day time to actually interact with people that interact with content.

    Great post, and kudos on the reviews. There were a few items I wasn’t as educated about that I should have been.

    All my best,


    • Tori,

      I do not consider curation a threat at all on a fundamental level. Even if all the content in the world was of high quality, there would still be a need for curation, because of the huge volume of content.

      The most important thing about curation is that it allows you to find what you are looking for, and that is not a threat to interaction and engaging, because once you find what you are looking for, you also find the author, with whom you can then interact.

      The imperfections of the tools we use for curation can be a threat, yes. Because of my background in philosophy, I’m used to considering ideals and fundaments, and on that level I do not see a problem.

      I checked out Buffer as you suggested, and read some of their blog posts as well.

      Interestingly, I had not properly considered the automation of that part of curation, sharing (although Triberr and paper.li both do it). When I’ve discussed automation, it has been related to content discovery or selection, not sharing.

      You are right, of course, that automating the sharing part is automation as well. However, at present it seems to me that this has more to do with the limitations of Twitter as a platform for curation: short tweet lifetime and the importance of regular tweeting. At the very least, I can see no possible objections to automating that part, unlike automating the selection of content.

      If I was able to discover enough content to share, I might consider using Buffer myself.

      • True enough, but don’t you agree, philosophically, that any time something gets automatically filtered and curated, that you’re running the risk of missing out on relevant content because you’re not doing the discovering on your own? (or perhaps because the powers that be restrict you because of technology or algorithms). I tend to agree with you that the potential for finding better content and thus having better interactions is possible, but I think the tools need to be refined before we can actually find something that is useful for both sharing and publishing.

        As for Buffer, I enjoy using StumbleUpon to find topics of interest, using my twitter followers to lead me to interesting articles, and then buffering the things that are the best. I will definitely be checking out a few of these tools, and will report back to you as well.

        • Philosophically, I suppose it depends on how you define filtering.

          Filtering as in using Klout scores to filter out messages from a large number of people: yes, you are correct, there is a definite risk to miss something. In my view, this is an imperfection in the tool used, although it might be the case that an ideal tool is impossible to create in practice.

          If you consider any algorithm-based searching to also be filtering (which is not how I have used the term here), then no, I don’t see the risk in the same way.

          If we had access to a super-awesome content discovery engine scouring a sea of near-infinite data, it would become a matter of granularity: in order to find meaningful information, you would need to define what you are looking for in great detail.

          If we assume that the search engine is also context-sensitive, then I could find information on, say, best practices for translating a blog using a professional translator instead of machine translation. I actually tried to find this the other day, but failed, because of the huge mass of translation plugin discussions, which I assume are also referenced in any content about human translation so negative keywords don’t help.

          This is what I mean when I say that I don’t consider curation a fundamental threat, as by definition it is about discovering and sharing valuable content, and filters are just tools to make the task manageable, and thus not on the same level of hierarchy.

          It seems to me that your concerns are ultimately about the tools, and on that point I can fully agree.

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  • Ville,

    Thank you for this excellent and detailed article. Really valuable insights. Another service you may wish to consider as it relates to crowdsourced curation is TrendSpottr (http://trendspottr.com). TrendSpottr identifies and curates trending content (links, videos, images, hashtags) for any topic or keyword from across Twitter and Facebook. The real value of TrendSpottr, beyond curation, is that it identifies early trending information, well before it has reached general awareness or popularity. In this regard, it provides users with access to the most early trending and curated content about the issues they’re interested in. Give it a whirl and let us know what you think.

    • Definitely an interesting tool and an interesting concept.

      I played around with it for an hour while listening to your blog videos, and although I can’t yet give a fully polished review, here are some thoughts on it:

      – I love the feature that allows you to check the tweets behind each trend. You guys introduced it to Scoble as well in the video, as you should, it is great.

      – I found a couple of interesting posts and news pieces, one on Triberr and another on Mikael Forssell being transferred to Leeds – I tried multiple fields you see. 🙂

      – When trying to find trends for more niche content, it doesn’t necessarily come up with any trends (it shows the tweets then though) and the ones that appear are not necessarily of such high quality. There was hardly anything on translation and localization, for example. Maybe they’re not discussed in Twitter.

      – Top trend for Klout was a re-advertised old Jeff Bullas blog post? Top trend for content curation was a fairly recent Jay Baer blog post that, while I considered it OK when it came out, is hardly spectacular? These are not really trends as in being anything new, they merely get a lot of exposure because of their well-known authors. I know that this is what you measure. As a side-effect, you end up with a bunch of uninteresting content in addition to new, hot stuff.

      – For services that allow you to spam tweets including the service name, there are lots of apparently useless trends. Paper.li trends becomes a list of most popular magazines; Klout trends become a list of +K tweets. Then again, these do get retweeted, so you do get exactly what you measure, and it might be useful in some cases. Often I’d like to know things about Paper.li when searching for it though: Any way to ignore something in the tweets? Like “Daily is out”.

      I think this type of tool perhaps works better for events around defined issues. For ideas, especially slightly niche ones, it tends to promote the big name who has advertised content with the correct keyword last. I also suppose services such as Triberr will affect the results?

      Overall, I couldn’t quite make up my mind about this tool yet. The concept is sound and interesting, but on which topics will it end up being useful for? It is unintuitive if auto-retweeting tribes can create trends. On the other hand, crowdsourced results depend on what the crowd is doing, there is no escaping that, it is their weakness even when it is their main strength.

      • Hi Ville,

        Thanks for your detailed feedback.

        As you suggest, our algorithms look at a number of factors, including: the recency, frequency, velocity & acceleration of content on Twitter and Facebook to determine trending value. For niche topics where there is either very little discussion going on or very little sharing or amplification (thus low velocity and acceleration), TrendSpottr will not identify any meaningful trends (as there are none) and instead show the source Tweet search results.

        By contrast, for more general topics (Social Media, Politics, Music), developing stories with lots of momentum (Libya, #j14, Arrington) and specific topics with consistent interest ($aapl, Infographics, #mufc), TrendSpottr crowdsources the most trending real-time content and provides early insights about stories that have trending or viral potential.

        Also, as you note, TrendSpottr is very useful for following large real-time events such as conferences, breaking news and festivals. For example, in Toronto, where we are headquartered, the Toronto Film Festival just launched. It’s a very prestigious festival and gets a lot of social media attention. Rather than trying to follow the #tiff11 hashtag on Twitter which is very difficult to manage, you can use TrendSpottr to follow the top real-time trending stories, videos, images from the festival. You can try it here: http://bit.ly/pumXcZ.

        We do limit the impact of spammers and repeat re-tweeters by filtering this out of our results. We also blacklist certain users and sites we’ve determined to be spammy.

        Finally, our core focus is on identifying early trending content and, in most cases, hours or even days before it has reached general awareness. We’re releasing some new features soon that will allow users to receive notifications and alerts when their topics of interest begin to trend or exceed a certain trending value. We’ll also be announcing some major partnerships with large content and data platforms soon. Stay tuned.

        Thanks again for your feedback and we hope you continue to use TrendSpottr to find crowdsourced curated trending content.


  • Anonymous

    Ville, thanks for mentioning Scoop.it (disc: I’m the CEO) in this interesting perspective looking at the right balance between crowd sourcing, automation and editorial control.

    As you noted, we’ve found an interesting balance between automation and editorial control by putting one before the other: our constantly-improving suggestion algorithm helps you find relevant content but you’re the one who decides what gets published.

    On top of that, as we believe like you crowd-sourcing doesn’t work for niche topics, we’ve introduced suggestions from other users. And that’s really powerful as while you can’t expect a niche content on an exotic topic to surface from crowd sourcing algorithms based on popularity, you can always connect with other users who share the same interest and will help you in your curation effort by making relevant suggestions to your topic. That’s something that works really well and which impact is growing on the platform.

    On the noise vs signal, our answer is to let users follow the topics they want and aggregate them on our explore page: this page is like a meta-magazine filtered only on your topics of interest. And while this is definitely an interesting reader, it also becomes a second layer of suggestions for curators as we introduced the re-scoop feature.

    Thanks again for the interesting perspective: not just listing the tools but reflecting on where this leads us to.

    • Guillaume, thank you for providing more details on Scoop.it, I really appreciate your work and think it is an excellent service.

      I’m also glad you liked my post!

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  • Thank you for this Interesting post Ville. I agree with the semi-automated approach to content curation. There is no way that algorithms will replace the human brain to determine which information is relevant. The future of content curation must allow each user to leverage his/her own experience and interests to identify, in the most effective way, highly relevant content.

    You should check Darwin Ecosystem (http://www.darwineco.com/). It’s a discovery engine for professionals needing to monitor specific topics. It captures recent information highly correlated to the user’s topic from all available sources. Then it presents the emerging themes on a single page, showing their patterns and correlations. This visualizations allows the user to consume large amounts of emerging content with no effort and to discover themes to explore.

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