Category Archives: linkedin

Is LinkedIn Mistakenly Passing Off Your Search Information?

I have a website and I have it in my LinkedIn profile. Recently I have noticed a few visits from LinkedIn to my website. But the strange thing is, the referer URL contained in one case the name of a person I know and in another case, the name of a person I don’t know. It’s not clear to me, whether the name in the URL is the name of the person searching for other people and visiting to their website, or the name of a profile from whom a person visited my profile and then to my website. Whatever it is, it made me concerned about it a bit.

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Filed under linkedin, Privacy

Vote No For Aggressive Viral Marketing

I received an invitation to NotchUp.com, a website trying to reshape the job market. I don’t have a problem with them trying to reshape the way we fundamentally have been doing things. What really annoyed me though is the fact that, even if I don’t want to be part of this network, some other friend of mine (and many others who I have never met in life but ended up my linkedin links and I wish I could upgrade/downgrade my links) can import all of his linkedin contacts so that NotchUp.com gets access to my information, without my permission! And why would anyone want to import their trusted friends list to NotchUp.com? So that they could earn 10% of what their friends earn by interviewing for the first one year. While I may certainly have a few good friends who won’t be tempted to giving away my information for that kind of a deal, I can’t trust everyone to have the same level of aversion towards this kind of practices.

Based on recent news about Plaxo mining data from LinkedIn in a similar fashion, I don’t know if there is a fundamental flaw in LinkedIn that is exposing the data or if that’s inevitable. The real problem is, unlike most security issues where there are 2 or 3 parties involved, in this there are 4 parties. LinkedIn, NotchUp, my link on LinkedIn and there is me. If the first three are doing things knowingly/unknowingly that gives them access to my information, however little that might be, without my consent, then forget Open Social. I value privacy more than portability.

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Filed under linkedin, NotchUp, Open Social, Plaxo, Viral Marketing

Should you trust LinkedIn recommendations?

Frankly, I don’t think so. The reason is, no one would ask reviews from people whom they think don’t have good opinion on them. Similarly, no one is going to give a public opinion telling the other person “hae, you suck big time, there is no way I am going to make the same mistake again, which is to hire you (as a manager) or to work with you (as a colleague)”. That is the very reason, you always see only very positive reviews and never any negative review.

So, to confirm my hypothesis, here is what I did. I looked at the reviews of some people that I worked with in the past and about whom I thought are not as competent and also know people who thought they are not competent enough. The reviews provided about these people by those who thought are not competent enough ended up giving good, if not great, reviews. Similarly, there were cases where people who hardly interacted with others within the company gave good reviews to some people.

Anyway, no one asked me to give recommendations so far nor did I try to get a recommendation. I think it’s meaningless. One co-relation I did observe though is, when people know they are going to get sacked, they try to increase their networking activity and recommendation seeking activity. And with reasonably good recos under their belt, they are well equipped to start interviewing with companies I guess. I am not sure how much weight employers are giving to LinkedIn recommendations. But, I wouldn’t certainly bother about them if I were recruiting. Just like I don’t give credit to some of the programming certifications that people obtain.

LinkedIn recommendations can never match the honest reviews provided for MBA application, for example, since in those recommendations, there is a way to waive the right to look at the recommendation. However, that model doesn’t work for LinkedIn because, the MBA application is a closed system accessible only to a specific school and a few individuals. However, LinkedIn’s recommendation system is sort of public.

This brings an important question. How honestly can the collaborative Web 2.0 solutions open for the public evolve? Perhaps in some areas they work fine. Some areas, they may not.

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Filed under linkedin

Why Google acquired Grand Central?

I don’t know the real answer. I like to pen down the main reason I can think of.

Let me first digress a bit. If you use LinkedIn, you would know that it’s possible for LinkedIn to create a profile of you based on the people you are connected to. This is in addition to all the personal details you provide about yourself. However, personal information like school and work will not completely distinguish two people. As the saying goes, “A Man is known by the Company he Keeps”, in addition to the personal information, the LinkedIn connections will give more information about a person.

The more accurate profile any company has about a person, the more it can target it’s services. For Google, that’s typically advertisement. With a service like Grand Central, Google will be able to amass the people relationships using the phone calls (A calls B). Currently, LinkedIn has no way to give weightage to a relationship. When two childhood buddies connect on LinkedIn that’s no different from when a recruiter hooks up with a person. Given that beyond that initial connection, the actual email communication happens outside LinkedIn, there is no better way for LinkedIn to establish additional weightage to each relationship.

On the other hand, the services offered by Grand Central allows it to track who is calling you all the time. The more calls you receive from a number, the more weightage can be given to that connection.

In addition, say you are trying to buy a house (well, now is not the right time to do so in many parts of the US at present, but say you are one of those who is still thinking of buying one). Now, if Grand Central figures out that you are working with some local real estate agent based on the calls you have been constantly receiving, Google can start showing you mortgage related ads, real estate ads etc. Ofcourse, they can do that based on what you are searching as well. But based on what it knows about that particular realtor, it can target even more.

Infact, Google has already been doing this with email. While Yahoo & Hotmail choose to not put any email address that you send an email into your address book by default, GMail does the opposite. It’s essentially cataloging all your network and the more you keep using Gmail, the more it can learn about you! By acquiring Grand Central, it not only knows your email network, it also knows about your phone network!

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Filed under Google, Grand Central, linkedin

LinkedIn, PersonRank & Google’s PageRank

I just accepted a linkedin invitation. At the bottom of the invitation email, there is a fact.

“Fact: People with 20+ connections appear in LinkedIn search results 14.6x more often”

That got me thinking and I ended up writing this article. As more and more people start using LinkedIn, and many just keep “networking” without really knowing much the other people they are connecting up at level 1, the whole linked in system is going to break at sometime.

If Google hadn’t invented PageRank, the search results would have still been bad (like those of Yahoo!, MSN which is now Live etc). So, I was thinking along the lines of a PageRank scheme for LinkedIn. That is, a system in which people linked from popular people themselves inherit some of that popularity. Just like how Google’s homepage get’s a perfect 10 on 10 as it’s PageRank, say the most popular people on LinkedIn get a LinkedIn Rank of 10. Now, I will get to in a minute what I mean by “most popular people” and how that is measured as this is critical for this scheme to work. Any person who is connected to this most popular person will get his/her rank increased a bit. So, a person connected to more and more popular people would him/herself get better rank.

Now, if we just go by how many people a person is linked to others, then that doesn’t really give a good picture. Mainly because, there are so many recruiters on LinkedIn who have more than 500 connections. Does that mean these recruiters should get a better LinkedIn Rank than others? What about those who just keep accumulating LinkedIn connections just for the heck of it? One guy for example, who was from my Alumuni and some 10yrs elder to me connected with me and I later realized that he did that just to promote his published books! The guy didn’t even bother to send a response to my personal email I sent as part of accepting his invitation! I wish LinkedIn has a way to retrieve back an earlier accepted connection.

Anyway, back to the topic at hand. I think, popularity should be determined by profile search and visits. That is, when people are looking for a particular profile, then that person is likely to be more popular. In this case, how many connections a person has doesn’t matter (ofcourse, they matter in calculating their rank indirectly based on the above scheme of connections from popular people, but that wouldn’t be linear and cumulative). Infact, popularity can be a combination of number of page visits + links to popular people. In other words, it’s a hybrid of Alexa’s Traffic Rank + Google’s Page Rank.

Let’s call it PersonRank.

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Filed under linkedin, social networking