I’m very excited and proud today to see my first blog post on AltSearchEngines as a guest writer. This is one of my most admired blogs and it is part of the amazing ReadWriteWeb blog network (RWW is #9 on Technorati top 100 blog list).
In this blog post I explained about the social graph and it’s usefulness for searching content, people and relationships. I showed some real world examples using the social graph in different ways. I discussed shortly the potential for the semantic side of this graph; there are several attempts going forward to making it smarter.
In the second part (coming soon) I’ll go over alternative ways for building social graphs to gain even more knowledge.
So here it is: Social Graph Search Engines Part I Applications
I will be happy to see your reactions.
See you somewhere on my graph:)
People leave missing information all the time. No blog About page, no employer name, no picture, no blogger name, Twitter account without web page link. Some time the simple link connection is not enough to piece it together. Your network too can help in finding connections or confuse people if your connections are spreads on more than one social network and accounts? In some cases it is done intentionally and no harm done but in others cases when done by mistake it could lead to lost traffic and opportunities. From what that I see and through my experience most times if the information is not just there, only few will bother looking for it. Isn’t bringing these connections forward and bridging information gaps the role of the new Social Graph Search Engines?
This post will cover:
Finding out how objects are connected across multiple web applications. Overcoming cases when the information falls between the web cracks or is deliberately missing. Looking beyond the trivial context of web links (URL), friends, fans or followers.
- Understanding the problems – some examples
- Looking what tools can help piecing the missing information together
- Bringing it forward – making it easily available when needed
Understanding the problems
Example 1 – me and my blog:
I did not add my blog URL to my LinkedIn profile. I did not add my employer’s name to my blog About page. I did it intentionally. I like to keep them separate for now. Omitting these two pieces of information seems to work so far. This missing information is not bridged by any social graph search engine that I’ve seen so far. It is ironic but a simple search of my name on Google will reveal the connection (warning: there are couple more Keren Dagans out there – both has nothing to do with software or technology). The connection in this case between me, my blog and my employer is my identity (similar profile info such as name, picture and location).
Example 2 – disconnected social networks:
I keep my Facebook and LinkedIn networks separate. I only have a couple of relatives overlap. I use Facebook for personal connections and LinkedIn for professional ones. I use Facebook sometime to post my new blog posts. It seems like social search engines can link between my friends across the networks, yet again, there is no association between me and my blog. Some information inside one’s activity can help making the connection.
Example 3 – multiple presence using disconnected accounts:
Case 1: My “personal” Twitter account is @kerendg. The other day I submitted a query to Twitter Search, searching for references to my other Twitter account @BlogMon. I found out that Stowe Boyd (stoweboyd) was asking “who is running BlogMon?”. The link to my blog is on BlogMon web page, and can be easily found using Twhirl or Twitter Search. I don’t know if he ever got an answer to this question or no. Soon after, I started following @stoweboyd using my @kerendg account (I don’t follow from @Blogmon). He did not contact me or follow-me on Twitter till this day- maybe because it is hard to make the connection or maybe it is just not that important. Your blog is an important piece of the new identity (FYI – WordPress using your blog URL for your OpenID).
Case 2: Some entrepreneurs runs both the start-up blog and their own blog. Only in few cases there is a link from the corporate web site to the entrepreneur’s (see Mashery -> Blogroll for Praxis blog ran by their CEO, Oren Michels – even this is not easy to connect). Same story using Twitter accounts (one for the business and one for personal updates). In LinkedIn organization is a connection. This is true across networks in addition to your role.
Example 4 – blog action:
Case 1 – comments: I don’t get too many comments on my blog. I can only wish to get more. Yet, I did get some comments from people with vast web presence. Is this some kind of connection? Did I Digg/Saved one of their blog post ? Did I mentioned their companies? You give me your attention I see it as another type of connection.
I also leave comments occasionally, mostly on the same 4 or 5 blogs. This information can help to understand my preferences. Similar interest is a another piece in the puzzle. Past activity on my blog too. Frequent reader is yet another type of connection with the blogger.
Case 2 – traffic source and blog reaction: I look at WordPress, BlogStats page. The section of Referrers shows traffic that is not coming from two type of sources:
- Unidentified – there is no way to track it back to the person that looked on my web site.
- Traffic from search engines
- Traffic from commends that I left (and there is no reply)
- Traffic from “similar post” links
- Traffic from incoming link to my blog from other blogs
- WordPress tags
- Identified – tracked back, with some luck
Since there is nothing to do about the first type of traffic (non invasively) there is nothing to add here, but for the second type: let the search begin…trying to find the source. Who dugg my blog? save it in reddit? is there a reply to my comment (like in Techcrunch comment threads)? Who mentioned it on Jaiku or Twitter? The information is scattered all over the net.
Most of my Twitters followers came through my blog. I added friends, people that acted upon my posts in other networks. I care about the origin reaction. When it is actually possible to track it back to the source, it involves a lot of leg work. Blog reaction is another type of connection . As I wrote about this before in “What is a blog reaction these days?” I don’t refer to “Blog Reaction” in the narrow definition of someone writing a counter blog post (pingback is a trivial link).
Some of the tools that are available today for piecing it together:
- Google search(Web) – searching for the person’s name, organization association – this is enough to discover presence across multiple networks.
- LinkedIn – searching for the person name and organization – looking at both profiles to cross reference with the other details to make sure that this is the same person.
- Google Alerts – add your link, blog name, your name, Twitter @account and link – looking for references.
- Technorati – looking for blog info and fans
- Twitter – this is a process
- If the information is coming from WordPress Referrer then you can follow it (unless it is coming from your account and not worth following)
- If not – you can search your link as is but it is better to try hashing it using TinyLink or http://is.gd/ or http://snurl.com or other URL shortening services. Use Twitter Search for that. Tip: select in all Languages – I found out that if this setting is not on a link search will return nothing even if the update is in English – the default.
- Use Twitter Search to search your name, and @account too.
- Delver – network graph – this service can save some of the leg work checking multiple networks.
- Jaiku – same as Twitter. What that is nice about Jaiku is that Google Alerts pick up on conversion.
- Flickr – some people like me don’t have account but do have tagged pictures submitted by friends.
- WordPress Referrer – this is the starting point
- Digg, reddit, del.icio.us and a like – go to your profile page and see who dugg/saved/rate your post
Do you know about more tools?
Now, wouldn’t it be nice if there was one tool that does all that and bring this information forward when it is most relevant.
Bringing it forward
If this information could be gathered through single tool then my ideal solution is something like SnapShots. When I click on any account, link from anywhere on the web present me with the graph. Show me this entity’s web presence. Show me how can we connect? This person blog, other accounts. The information could be context sensitive – e.g if I’m in Twitter show me all Twitter accounts for the same entity – show me if we are connected through Twitter first.
Alternatively, send me an alerts about subtle semantic links to me and my blog. Something like.
- This individual
- from this location
- working at
- in this role
- own this blog
- x degree from you on Y network
- was once at your blog before
- looked at your blog on this post
- you profile in LinkedIn
- your other Twitter account
- respond to your comment
- dugg your blog.
- Do you want to make a “trivial” link and connect?
- Go to his blog
In this post I was trying to explain that if we want to build a complete social graph network it is not enough to look only on the “trivial” links. This is just the beginning. It will not present a full picture of one’s web presence and identity. In order to construct a useful graph there is a need to look at other type of links. These links are scattered across multiple social network and services. They are part of the enhanced meaning of one’s profile attributes including activities and relationship.
I see three steps moving in this direction. The first is piecing someone’s identity drawing on information from multiple sources. The second is using this information for finding new ways that people are connected i.e. building the complete and rich social graph. the third is presenting it when relevant.
I did not cover the uses cases for having such information at hand. On top of my head I can think of a few:
- It could be handy to QA web presence – especially if the entity is a business
- It could be handy for web-sites to understand their crowd
- It could be handy for business development
- RT @jameskobielus: "5 reasons why Spark Streaming... is not stream processing" ( ow.ly/KGAfj) JK--See also my recent post (http:/… 2 days ago
- Where big data goes - streaming infoworld.com/article/290050… #ESP 6 days ago
- RT @InfoQ: Making Sense of Event Stream Processing bit.ly/1GGL0L4 1 week ago
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