Deadline and Prizes for the Sourcing Challenge

booleanstrings Boolean 0 Comments

win

As I have promised, here are the formal rules for the Sourcing Challenge.

Answer the questions in a comment here – Are You an Advanced Sourcer or Researcher? Partial answers are welcome; you do not have to post all the answers in one comment. It’s OK to add an extra comment where you change your mind on an answer as well.

The post has 12 13 questions. Each correct answer to a question gives the participant one point, except the correct answer to the question number 4 gives a whole five TEN points. Also, I have added one more question – #13 – also TEN points.

The first person to answer each question correctly gets one additional point. The answers need to be explained.

The person with the largest number of points is the winner. In the case of a tie, we’ll take a look at the explanations; we might have more than one winner, too.

The prize is a choice of a one-hour consultation – where we can source together, or talk about sourcing tools and tips – with your choice of: me (Irina), David Galley, or Martin Lee; access to one webinar of your choice from our Training Library; and participation in our new tool Beta-testing (now, developed in a stealth mode).

Additionally, here is the grand prize for anyone who answers all 12 questions correctly: access to all of our Training Materials.

Deadline: Monday, October 24th, 2016.

Best of luck, Sourcers!

Are You an Advanced Sourcer or Researcher? Can You Answer These 12 Questions?

booleanstrings Boolean

researcher

 

Hello Sourcers and Internet Researchers:

Here are some questions, that I would like to offer, based on just one collection of professional data, that has an interesting implementation, and that is – documents uploaded to LinkedIn by its members.

How good are you at understanding what data can be found and how?

Please post your answers as comments – and please provide your reasoning for the answer. Responses to only some of the questions are welcome. I anticipate a nice discussion here!

[Updated!]  We have launched a contest based on these questions!

Deadline: Monday October 24th.

Here you go:

If a LinkedIn member, say, Joe D. wants to upload a resume (or another document) to his profile from his PC, LinkedIn will ask him whether he would like to store the document on Slideshare or not. (If you haven’t, try it, you’ll see.)

Suppose Joe said “no” to posting the resume on Slideshare and uploaded it to the profile. When we view Joe’s profile, while logged-in, we now see Joe’s document’s preview as an image (or series of images if there is more than one page).

  1. Joe said “no” to storing on Slideshare, so where (to which site) did it go?
  2. Is a preview available on Joe’s public profile? That means, is it available when you are not logged-in?
  3. Can the preview image(s) be viewed in an incognito window, i.e. without logging into LinkedIn?
  4. [Difficult] Can we download the original resume or document (say, PDF or Word)? From which site? Please note, the question is about finding the original doc, not trying to recreate it by using “print to PDF” or character recognition. 10 points
  5. (Easy) What does LinkedIn call the part of the profile that stores those uploaded documents?
    • (5a, harder) Is there a URL pointing to that part of the profile (for logged-in members)?
  6. Can we find Joe’s profile by searching on LinkedIn “people search” …
    • (6a) for the resume keywords, if they are not included elsewhere on his LinkedIn profile?
    • (6b) for keywords in the title and description, that Joe adds when he uploads the document to the profile?
  7. Is there a URL that you can share with a colleague, for them to see the resume if the resume has more than one page, for example, three pages, – not on LinkedIn, but on that site, that stores the resume?
  8. Will Google find the uploaded original document if there are no other copies of it online? The options are “yes,” “no,” and “sometimes, when…”
  9. (This is a tough one!) Will Google find the uploaded original document’s image preview in the Image search? The options are “yes,” “no,” and “sometimes, when…”
  10. Can Yandex find Joe’s original resume?
  11. Can Bing find it?
  12. On which cloud is the document stored (Amazon, etc.)?
  13. BONUS Q: If a LinkedIn member opts-out of Slideshare when uploading a document, the document is still posted on Slideshare (as we now know) under some “user” account. With what email domain has that “user” registered with Slideshare? (you might want to find that user’s profile URL for starters). 10 points

To help you here’s a (randomly picked) example of a profile with an uploaded resume.

What say you? 🙂

I’ll reveal the answers in a future post.

-Irina

P.S. Just launched a formal contest around these questions. I think, these are great questions for anyone who searches, to understand the Surface, Deep, and Dark Web.

Advertising as a Researcher’s Friend

booleanstrings Boolean

advertising

Not every advertising option is equally useful for research, and I don’t think truck advertising or billboards can play a big role. But some other advertising platforms can give us invaluable data – even before we invest any money in them.

The two social networks with giant amounts of professional data, LinkedIn and Facebook, offer to explore to whom to advertise. While we do that exploration as the potential users of the ads, we can assess available talent pools. This is a largely underutilized resource to use in research.

Take a look at these screenshots of the dialogs to help define the audiences for advertising. These dialogs can answer the questions any self-respecting Sourcer would try to answer before looking for candidates:

Where are the skills we are looking for? – Companies, job title, locations, graduates from which schools?

(To illustrate the ad audience exploration capabilities in the screenshots, I have inserted some parameters, such as target company names, skills, etc.)

LinkedIn Ads (note – this data is available to any user, even the basic):

linkedin-ads

 

Facebook (this data is also available to anyone):

facebook-ads

 

For each entered set of parameters – locations, employers, skills, and more – these tools show us the available pools of professionals. Spending some time with these and similar tools is a solid way to get some market intelligence data – and to be much better prepared to source for individuals with target skills.

Nerdy Custom Search on GitHub

booleanstrings Boolean

github

Ever since we started making use of structured web search capabilities, I have been fascinated by the precise results we can obtain from a general search engine via this mechanism.

Here is an investigation and multiple examples of precise X-Raying on Github.com, which is a truly useful site to know if you are looking for software developers.

For those (few) Sourcers who love working with advanced search operators – here is where you will find tons of long and barely readable expressions, that you can change to your liking! For your convenience, I have placed a search box for Custom X-Raying Github below as well.

For those who’d rather skip the cryptic search syntax, the good news is that we have a new, unique Sourcing Tool in development – currently, in a stealth mode – that will relieve end users of needing to use these operators. (Please follow us for more news!)

For now, just take a look at the search results. You will find them to be precisely finding what we are looking for in each case – a big difference with “general” Google and most social sites.

Here you go:

Examples – Github Precise XRay Member Search

Want to build your own? The Custom Search Engines Webinar is coming up!

And here is a

Github Custom XRay Engine


This Webinar will Change the Way You Source

booleanstrings Boolean

google

“Like writing poetry or tweeting, searching without operators allows us to be creative and make discoveries.” – David Galley

Searching without Boolean is a new webinar with how-to, step-by-step guide to creating amazing searches in English; here is a quick write-up on its content.

If you search the Web on a regular basis, you will want to obtain the webinar materials, to instantly improve your sourcing performance. Promise, you will never search like you used to! Tune into the best ways to build queries, that are now simpler and cleaner than before, yet produce superior results.

Recruiters: want to get on the phone with potential candidates fast? The webinar teaches more than a dozen easy to use “plain English” search patterns, which do not require advanced search skills. (But they do require thinking it through and understanding what to expect; we’ll go over that in the presentation).

Major search engines, including Google, are rapidly becoming more semantic-oriented, meaning – they try to guess the intent of the person who Googles and respond appropriately. In many practical cases, Google is now giving better answers to searching “in English”, without advanced operators, than when using complex Boolean constructions. That’s great news!

At the lecture, I demonstrate finding “hidden” professionals, locating and exploring previously unknown sites full of candidate details, by using creative patterns and templates, searching in English “without Boolean”.

Equipped with the search patterns that are easy to keep in mind and apply, you will be able to put your new skills to work as soon as the webinar ends.

Who should attend: Recruiters who need to find target professionals outside of the mainstream sites, but dislike or don’t have enough time to write complex Boolean Strings. Everyone who wants to find more professional information on the web by using additional search patterns.

Included: The slides and video recording from the session(s) for you to keep and one month of support for any questions about the Boolean free Sourcing techniques demonstrated in the webinar.

The webinar materials are available (including one month support): Searching without Boolean.

Search Like a Pro in Three Simple Steps

booleanstrings Boolean

rocketscience

Want to search the Web like a Pro? Here is a fast way to get there.

Searching the Web is not Rocket Science. Everyone can learn to search even for complex information, such as professional bios, quite efficiently, following the three steps that I am about to describe. And the good news is, you do not necessarily have to use advanced search operators to find excellent results.

Steps 1 and 2 are required to prepare to search, while Step 3 is actual searching.

Step 1. Identify where you want to search.

The web is so large – just Googling some keywords, that you would like to see on target profiles, is a long shot! The first step is to narrow down the set of pages where you would like to find the results. A traditional technique for this step is only to look within a given site. Searching only within a given site, using a search engine, is called “X-Raying.”

(Whether you are or are not familiar with the operator site:, just read on. You won’t necessarily need to learn about search operators.)

To find a site that you might want to X-Ray, you can start with a profile you have already found – perhaps linked from another profile or shared by a colleague. Or, if you are starting from scratch, run a simple Google query describing a site. For example, Google for [association of accountants in Canada] or [members oil gas Louisiana].

Step 2. Create a search template to search just for the desired pages on the site.

For that, it helps to take a look at a few profiles on a site (that’s if those are your desired pages) and see what these pages look like; then, use that to start constructing a search. Let’s take a look at an example.

Here is a sample profile: http://www.mosaichub.com/member/p/jim-ervin.

For people who are familiar with the “formal” X-Raying (i.e. using the operator site:) – from looking at the profile, you will see how to proceed to narrow the search down to this type of pages – at least in this example. You can take advantage of the URL structure:

site:mosaichub.com/member/p

For those who don’t want to use any operators: use the domain and add a phrase or keywords that any profile on the site would have. Example:

“mosaichub.com” “member profile.”

Either of the two sample strings above can serve as a search template.

Depending on the site you are looking to explore, you may find that the site’s profiles have a phrase like “member since”, “connect with”, or “full profile it’s free” (etc.) – those would be the phrases to use in the template.

Step 3. Now you are ready to search.

Add keywords, such as job titles, locations, and skills.

Examples (using the two templates we had created earlier):

You can repeat the search varying the keywords and phrases, to uncover the pages that you want to find. Here’s a diagram with several more examples of the three-step search construction (no Boolean operators are involved!):

searching

For an in-depth exploration of fast and productive searching without special search operators, please join me at the upcoming Webinar

Searching without Boolean

(Lecture – Wednesday, September 7th, 2016. Practice – Thursday, September 8th, 2016. Seating is limited.)

If you do know how to use advanced search operators, I invite you to join as well – to review your search templates, learn how to simplify your searches, and get the results fast.

 

 

Who Offers Proximity Search?

booleanstrings Boolean

google-bing-yandex

Finding several terms that are close to one another is a way to make the search results more relevant, i.e. make the search more semantic. This feature is called Proximity Search; it’s especially useful when searching on the web and in long, unstructured documents. A familiar example is to search for the word manage close to the word people, to find bios of those who have managed people, vs. profiles that just have both words somewhere in the text. Another example would be to look for a school name close to the year of graduation. Applications of proximity search are multiple.

Google, Bing, and Yandex have all implemented proximity search features. It looks like, however, the first two search engines have dropped the ball. Let’s take a look at some examples.

Google’s has never officially documented its proximity operator. Back in 2010 researchers were excited to read the post “AROUND has always been around” by Google’s Dan Russel. At this time, however, after looking at multiple test searches, I’d say AROUND doesn’t do its job. Compare, for example, these (randomly picked) searches on Google:

  • manage AROUND(9) people “associate partner” accenture atlanta
  • manage AROUND(1) people “associate partner” accenture atlanta
  • manage people “associate partner” accenture atlanta

The results are just identical:

proximity-google

Perhaps there are some cases where AROUND does influence the results, but the operator is certainly unreliable!

The same goes for Bing’s (documented!) operator NEAR. Just compare these simple searches and you will see that it’s not working right:

proximity-bing

Let’s hope that Google and Bing engineers will make the proximity search feature a high enough priority to fix it sometime in the future.

Yandex.com is the only global search engine that does, in fact, currently support proximity search. For starters, Yandex has the operator & which means “search for the terms to appear in one sentence.” Here is an example I have just created in response to a question on the Boolean Ning Network:

“graduated” & “Georgia Institute of Technology” & 2016

Further, Yandex can search for one term after another, within a certain “distance” in words between the terms. This search –

“Georgia Institute of Technology” /2 2016

will look for the second term (2016) to appear after the first term (“Georgia Institute of Technology”) with no more than two words in-between. You can also search using (for example) /(-2 +2)  to find the terms in either order, within two words from each other.

Conclusion: Yandex wins! If you are looking to use proximity search on the web, Yandex is your search engine.

Your comments and creative proximity search examples are welcome!

 

Have You Retrained Your Team on LinkedIn Recruiter?

booleanstrings Boolean

lir

The new LinkedIn Recruiter (LIR) has some interesting and useful features. Unfortunately, it also offers unique search syntax that is hard to remember or understand.

Here’s an example. Guess which job title search will provide more results:

  1. Software Engineer
  2. Software Engineer NOT Senior

If you said “1.”, you are wrong – it’s the 2nd search that will return more results, and here’s why. When we type (just) Software Engineer, LIR automatically assumes that we are searching for a phrase Software Engineer.” But if we use AND, OR, or NOT, it doesn’t assume so. Therefore, the first search will not return (for example) Software Development Engineers, while the second search – would. The search syntax is not intuitive and not consistent with the syntax used in personal and business accounts – and is also not consistent with what it used to be in Recruiter.

The above is probably the most confusing part of the new design; I have described it in a recent post – Beware of the “Smart” LinkedIn Recruiter Search Syntax Change.

Interestingly, the new LIR has kept the “true” Boolean in the keywords search (and also in the only available documentation). If you want to stay with the “normal” Boolean syntax in LIR, there is another opportunity to do that: within “Filters” in Projects, the syntax remained as it used to be. But using a project’s filters is not a very powerful way to search because the profile previews are short.

By now, unsurprisingly, we have heard from multiple recruiters that the search results are not what they expect them to be in LIR.

Additionally, the feature I liked, the toggle between a search dialog and the Search Insights is gone. The “Search Insights” is still there (though it’s now hard to find), but there’s no easy way to switch between the two views.

The new LIR has also lost the valuable display of the distribution of the search results along the facets, such as the current or past company, location, and more. I.e., if you enter some qualifications and want to know which companies employ your target potential candidates, this is no longer possible in LIR.

There’s a lot more your team needs to be aware of if you are LIR subscribers. Join me  – and many of your colleagues – tomorrow at the webinar “Mastering LinkedIn Recruiter” where we’ll go over all the necessary skills, knowledge, and productivity tips (many of which are not part of the help documentation) that you need to navigate the Recruiter.

(If you miss the webinar – no worries – the recording, slides, and support will be available on our SourcingCertification site).

10 Little-Known Strings to Mine Member and Attendee Lists

booleanstrings Boolean

member-list

Many Sourcers know how to locate lists of professionals in Excel format by using the operator filetype: and the typical column headings, such as name, title, company, and email. Indeed, by adding keywords to a search like filetype:xls name title company email we can find lists of professionals whose background we can further investigate to see if they match our requirements.

There, however, lots of other ways to search for lists, that we can come up with, based on creative thinking and common sense combined (which is always a good recipe for successful sourcing!).

It will be up to the reader to figure out why these strings work and how to adjust them to work for your cases – but it shouldn’t be hard. Here you go:

Sorted Lists

Updated Lists

Email Domains

Personal Names

Job Titles and Abbreviations

The possibilities are endless!

I will be sharing numerous ways to mine lists and professional profiles both from the Surface and Deep Web in the special repeat of our most-attended lecture ever – “Sourcing without LinkedIn” on July 27th – don’t miss it!

LinkedIn Network Trimming

booleanstrings Boolean

networking

LinkedIn is automatically removing many connections between its members today, July 18th, 2016, following an email it sent to all “mega-connectors” (including me). A copy of the email LinkedIn has sent to mega-connectors about the Trimming Project can be found, for example, in these blog posts: Further LinkedIn Changes Agree Or Disagree ? and Why Is LinkedIn Blowing Up My Network?

Some members think that cutting connections is “Microsoft influence”, but I don’t think so; it will probably take a while for Microsoft and LinkedIn to finalize the deal. Reducing connections was not surprising, as the next logical move after recently stopping the largest networkers from growing networks further.

Before I proceed to write about today’s network reductions in more detail, let me say that I am not annoyed that LinkedIn is doing that. Consider these two points:

1. Our real-life connections with fellow professionals do not equal our LinkedIn connections, and, of course, we can keep them even if the computer-recorded ones are gone!

In the end, connections on LinkedIn amount to computer-stored information. “Connecting” and “messaging” functionality has provided ways to form and expand business relationships (thanks to LinkedIn!). It’s a tool that helps, but then it’s up to us to work and communicate with others in real life to each others’ benefit.

2. LinkedIn is a business making significant income from InMails, i.e. messages between the members who are not connected. It’s only natural that LinkedIn won’t want  “too many” connections between members.

(Additionally, due to recent functionality changes, larger networks on LinkedIn have lost their advantages. For example, now only a small percentage of mega-connectors’ connections – and “followers” alike – are notified of the posted blogs and status updates. Instead, posts that make it to everyone’s streams are the ones most commented on.)

LinkedIn has created and continues to grow the world’s largest social network for professionals. I see some current functionality problems and some desired functionality added as more important that cutting down connections. (I’ll write another blog about those.)

With all that said, let’s get to some details on the LinkedIn Network Trimming project.

There’s no way to estimate precisely how many mega-connectors (members with 30K+ connections) there was before today, but the number was probably at least in the thousands.

Connections that LinkedIn is automatically removing today are the ones mega-connectors have made more recently. This is unfortunate because the most recent connections have often happened around some latest business discussions.

With a connection is removed, here is what to expect:connection-removed

I.e., if you are a mega-connector – or recently connected to someone who is a mega-connector – you are losing all of each other’s contact information (phone numbers, physical addresses, Skype IDs, etc.).  The notes and contact info of the 1st-level connections, except for email addresses, is information that was never possible to export, so it is just gone. You also won’t be able to send messages to each other any longer; it will have to be InMails.

As an additional side effect of removing “extra” connections, expect everyone’s visible networks to become smaller. LinkedIn search results will show more anonymous results (those “outside of your network”) than before.

It’s a good moment for mega-connectors, “LIONs” to rethink how they want to proceed!

As a temporary “stay in touch” mechanism that I have shared with some of my connections, please “connect with me” here on the blog. Also please feel free to join our Boolean Strings Facebook Group.

-Irina

P.S. Interestingly, someone has forwarded a LinkedIn Rep reply when he enquired about removing connections. Here it is:support