Tech Sourcers: Watch Github Profile READMEs

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Good news! Github has added an ability to create an informative bio for its users. They call it Profile READMEs. We can hope Developers will post some detail about themselves so that Recruiters reach out to the right people. 😀

Adding a bio is straightforward – you need to create a repository with the same name as your username and drop a Readme.md file there. That file’s contents will be shown on your front profile page – publicly.

From Profile readmes, we can get extra info about members, including their skills and preferences, and often, public email addresses. Here is what a typical Profile readme looks like when displayed on the profile home page:

Since most people will follow the template for a readme file that Github offers, we can expect at least parts of the phrases from it to be kept in the bio. It starts with “Hi There” and has several phrases to be finished such as “I am currently working on…” “Ask me about…” (I did).

Using the phrases, we can X-Ray for bios or search on GitHub itself:

site:github.com “hi there” “how to reach me” “gmail.com” python

“hi there” “how to reach me” python

Members whom you find this way have publicly displayed background and contact info. They are easier to assess as potential candidates and will not mind an appropriate email. Hopefully, members will actively use the feature.

 

Image Diversity Sourcing with No Photos

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Those of us who source for diversity know that reviewing profile photos is one of the key filtering techniques in sourcing for several kinds of diversity. But today, I want to tell you how to find some female candidates with no photos included.

I came up with this hack while sourcing for a Director of Data and AI in Berlin, whom the client would like to be a woman ideally. (It is a very male-dominated field.) I noticed that public XING profiles without a picture have two different generic images depending on gender. So here is what you can do to find women without a profile picture – search by a generic female image while X-Raying XING:

(My friend Glenn Gutmacher noticed that this type of search starts doing something odd when you use phrases in quotes or operator inurl:. Make sure you screen your results.)

Another such site is Healthgrades. It allows the same sort of search for females:

Searching in images and by images gives you an additional sourcing boost. There are more results in image X-Ray searches (typically, twice as many). Research, translation, diversity sourcing, and a free filtered LinkedIn member search can be implemented through image tools. Additional scraping and “in-scraping” (following links for data) will make your X-Rays perform better than searches in LinkedIn Recruiter.

Sourcing nerds and all those who want to source in less-traveled places –

Check out our brand new webinar, “Sourcing in Images!”

How to Exceed 1,000 Search Results on Bing

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Guest post by Glenn Gutmacher

In a recent post, Irina described an intriguing follow-up to a discovery made by Dan Russell. In short, the initial discovery was that Google used a completely different index to store its web-crawled image results from its index of regular webpages. What Irina realized is that the same query run on Google Images could yield very different results than on regular Google search.

Why that’s significant, as she explained, is that you might get only a limited number of results from, say, a regular LinkedIn x-ray (site: search), but if you ran that same search on Google Images, you’d find many additional relevant results missing from the regular results. Using simple web scraping and filtering in Excel, you can quickly get all the unique results out of the combined set. It often exceeds 1,000 results in total — the maximum that Google used to return in the old days, but rarely displays even a third of that today!

SO WHAT’S NEW TO LEARN?

Why was I invited to write this guest post? Because Irina and I discussed whether this phenomenon might be the case on other search engines, and I agreed to help prove it on the other biggie known for good LinkedIn search results: Bing.com.

I used Bing’s default Safe Search: Moderate filter in all cases. For Bing’s default (“All”) search, I obtained 997 results for her same query of site:www.linkedin.com/in “registered nurse” dallas tx

Note that the total is significantly more than the approximately 350 that Irina reported for this query on Google (I got 313 results when I googled it). This alone might motivate us to use Bing for more LinkedIn searching!

However, it gets even more exciting when you add in Bing images search. To be as apples-to-apples as possible, I initially used Bing Images’ filters to try to match the same criteria/settings that Irina used in her Google test: People à All (this gets faces as well as photos) and image size of 200 x 200:

https://www.bing.com/images/search?q=site%3awww.linkedin.com%2fin+%22registered+nurse%22+dallas+tx&qft=+filterui:imagesize-custom_200_200&form=IRFLTR&first=1&scenario=ImageHoverTitle

This yielded 485 results. However, I found that searching images with the same query but without any filters yielded a few more results (total of 507, or 22 additional), but all remained solely LinkedIn individual people profile results, given the specificity of the site:linkedin.com/in portion of the query.

THE BIG REVEAL

Now for the amazing conclusion: of the 507 Bing image search results and 997 regular Bing search results, the overlap of URLs was only 10. Yes, ten!  So that provides 1,504 total profiles, and the astonishingly low 1% overlap is remarkably similar to what Irina found in her Google test.

I should note there were a handful of false positives in both the regular and image search results where the profile was not the page of a registered nurse nor someone in Dallas. However, it wasn’t really an error because if you looked in the “People also viewed” right-hand column, there was inevitably one Registered Nurse and yet somebody else with a Dallas TX location! In any case, this doesn’t take away from the fact that the LinkedIn results generated from the image search were almost all *completely different* than the regular results.

So it appears that both Google and Bing are harvesting and processing images in a completely different way than other content, and it would behoove all sourcers to search each filetype if the goal is exhaustive, unique results for your query.

My thanks to Irina for inviting me to write this, and I hope we can do it again sometime on another sourcing topic!

Editor’s Note: If you are not familiar with the common methods to download and deduplicate results like this, you can learn to use scraping tools in our class on December 8, 2020.

About the Author: Glenn Gutmacher was one of the early online sourcing trainers (back when it was called “internet recruiting”) and started one of the first job/resume boards for a New England newspaper chain in the ’90s. Since the new millennium, he has been a full-time sourcer or sourcing manager in multi-year stints at several multibillion revenue companies including Getronics, Microsoft, Avanade and currently State Street Corporation.

Hack: How to Get More Than 1,000 Results on Google #OSINT

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While the official displayed results limit is one thousand, these days Google searches never produce more than 300-500 results. But today, I ran into something interesting: you still can get many more results, and even more than a thousand.

The secret is to also search in Images.

If you thought that when you switch to images on Google’s search screen it will pick the indexed images from the displayed results and show in the same order, you are wrong. As we have already learned, images is a different database.

I have switched to Image search, collected results, and compared with the general search results in some tests to arrive at the following:

  1. In images, you can get a lot more results – close to 1,000!
  2. Results in “all” and images overlap very little! If you combine them, you will easily get over a thousand results.

A search that I ran in one of the tests was as follows:

The results were astonishing. Google search brought in about 350 profiles. Image search – almost 800. And, the overlap was only 14 profiles. So, combined, I got over 1,100 results.

How do you collect, combine, deduplicate, and filter results?

It is straightforward if you use scraping tools. Join us for a class on December 8, 2020 to learn about them!

Three Easy Ways to OCR

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Sometimes we need to get the text out of an image (such as the one posted above, a document scan, a screenshot, or a photo – think a group picture with nametags, for example). It is just inconvenient not to be able to search within “image-documents” or parse them.

I have good news for you. Character recognition is a solved computer task. There are several convenient ways to address the challenge.

  1. Upload to Google Drive.
    • It will convert your image to text upon uploading.
    • It is far from perfect, though; most formatting will be lost
  2. Google Cloud OCR recognizes formatting.
  3. Yandex Image automatically OCRs when you search by image:

Do you have a favorite OCR tool?

I will be speaking about creative sourcing in images at Sourcing Summit Germany – please come listen if you are attending!

My blog readers: would there be interest in an Image-focused sourcing webinar?

Including Unemployed in LinkedIn Searches

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While Recruiters typically avoid reaching out to unemployed prospects, this year is different. However, if you search for the current title or company, you will not find professionals who have lost their jobs due to COVID.

Here is how to include them.

On LinkedIn, search using keywords and other filters but not a current title or company. On Recruiter, also, do not use years of experience, at the company, or in position.

What about X-Raying? For people with a current job, LinkedIn public profiles show their titles and companies. For people without, public profile titles include their school in the format <name> – <school name> – LinkedIn:

So, if you X-Ray for a school name in the page titles – site:linkedin.com/in intitle:”university of chicago” – your results will include the school’s alumni with no current jobs. Unfortunately, your results will also include the school’s employees. But if your target audience is outside of people in Education, you can reliably find unemployed by X-Raying. Optionally, add #opentowork to narrow your searches.

P.S. Adding or excluding the word “present” in LinkedIn X-Ray does not help find profiles with or without current positions because the word is added to the profiles by JavaScript. Google often does not index it, and neither does Bing.

All that said, if you are a job seeker, it is best to keep your current job “open,” to be found more often. We will understand.

Facebook Photo Discoveries

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While you can magically find photos with any given number of people on Facebook, clicking on them (in Google’s image search) lands on the page, not the photo itself. You have to scroll down to find it. As I have found out, to find “just” photos (or rather, pages with one photo only), you need to X-Ray in a more specific manner, namely,

site:facebook.com/*/photos/a (add your keywords).

Here is an example of precise people counting by Facebook. Another example (suppose I am sourcing in Healthcare):

site:facebook.com chicago hospital “from left to right” “image may contain * people”. You can see a screenshot of the results above.

Once you land on a page with the photo in question, you will often see who who has posted it and often, who is on the photo, who liked it, and who commented.

You can find pages like these:

and

You can then collect the data and engage with selected “likers”.

(To narrow to profile photos, if you were wondering, try this: site:facebook.com/*/photos/a “updated their profile photo”.)

My example strings find images but you can, of course, run them in “all” searches.

Hack: Google for Facebook Photos Interpretations #OSINT

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Based on the following two behaviors from the tech giants:

  1. Facebook interprets pictures and inserts the interpretation into its public pages HTML code
  2. Googlebot indexes these interpretation phrases

– you can reveal lists of members’ names and profiles based on Google’s image search.

The two Facebook phrases most common for tagging photos are:

  1. “Image may contain… “, for example, “image may contain 7 people.”
  2. “Text that says,” for example, “text that says right to left.” 

As an end-user, you cannot see the phrases on the pages, but they appear in Google’s indexing. (I will skip discussing the reason.)

Example X-Ray (note that I am searching in “photos” for better results):

Try a similar search and count people in a picture. Facebook is excellent at recognizing and counting us!

(You can also search for cats, mice, elephants, or fights, guns, and other things. It is an OSINT technique for sure.)

Now, make the search more useful by a) customizing to your recruiting needs and b) specifically looking for pictures where people are tagged. Use your target terms, words pointing to lists, and words for photos with people. It can be a hit and miss; vary the strings a lot. Example:

Here are some example lists you can uncover (one more is at the top of the post):

(Zoom “selfies” is a category of its own!)

Your comments are welcome!

Eleven Diversity Sourcing Exam-Like Questions

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In 2020, Diversity is on everyone’s mind. Our first run of the Diversity Sourcing Training and Certification Program has exceeded our expectations in the way it has been received. We have an audience of thirty eager to learn recruiters. They show a “can’t wait to put my hands on it” attitude, which every trainer loves. They ask questions. They tell us that they love the program; not a single one has complained. The first seven people already graduated with a CDSP credential.

Our next program run is scheduled to start on November 10, 2020 and . Again, it will be limited to 30 people. Visit the page to sign up.

Soon, we will look at scaling up the program to have fewer monthly limitations.

I want to share with you some examples of the questions participants may get at the exams. (No, you are on your own!)

As you can see, all questions fall into six categories in application to Diversity sourcing:

  1. Exploratory Research
  2. Google Search
  3. X-Ray
  4. LinkedIn
  5. Social Sourcing
  6. Cross-Referencing

These questions are similar to the ones we have been giving at the general Sourcing Certification Exams.

Have fun:

  1. This woman is Director, Consumer Banking & ME Region Exec, Bank of America, and moderates a “Meet the Experts” panel at a conference of which association (enter its URL)?
  2. How many members of vetfriends.com by the name of Mark Jones served as Coastguards?
  3. The first African American to serve on the board of Alphabet and Google was formerly a partner at which consulting firm?
  4. This member of Anita.org – https://community.anitab.org/author/natashagreen25/ – is the owner of a company that gives lessons in:
    – PowerPoint
    – Greek
    – Archery
    – Scuba diving
  5. The Gulf Coast Minority Chamber of Commerce has a business directory listing a person from the Navy Federal Credit Union. What is her top endorsed skill according to her LinkedIn profile?
  6. What is the closest number? In the United States, minority-owned businesses enterprises make up about X percent of the nation’s total businesses.
    A. 2%
    B. 15%
    C. 20%
    D. 33%
  7. According to LinkedIn, what is the top college that employees of White Mountain Apache Tribe graduated from?
  8. How many people have “Diversity & Inclusion Officer” as part of their job title on LinkedIn, live in Washington, DC, and are interested in joining a non-profit board?
  9. How many African American CEOs are there among Fortune 500 companies?
  10. How would you complete the string to X-Ray for members of the International Association of Women? site:*
  11. This woman is a Chapter President of the Alaska Chapter of the American Indian Science and Engineering Society. What statement describes her employer most closely?
  • “Alaska Natives”-oriented association
  • Oil pipeline transportation company
  • Supply chain management
  • Public relations

Diversity Sourcing: Bird’s Eye View

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While we always “search for what we expect to find” as “the” approach to any sourcing, Diversity sourcing has its unique characteristics – and it is not easy. Here are the main points that stand out in our sourcing practice. I believe they are universal. Let me know what you think.

Diversity sourcing primarily relies on two techniques:

1. Long OR searches

Examples:

  • Ethnic or female first names
  • Ethnic last names – for example, Hispanic or American Indian
  • Names of colleges – Historically Black, women-only, etc.
  • Diversity associations, events
  • Use these on LinkedIn.com or Recruiter
  • Since Google’s ORs are limited, utilize Custom Search Engines

Finding the terms for OR statements is easy; just Google.

2. Advanced image search

Three things to keep in mind:

  1. You must review each result and look at the photo if present.
  2. You will see false positives pretty much for any specialized search.
    • Why? Because some first names can be women’s and men’s; men can belong to women’s organizations and attend women colleges; white men can attend diversity universities, etc.
  3. Important! Any specialized search restricts results to a small subset of what you want to find. The majority of diverse candidates do not tell you how they are different in social profiles or resumes. They do not have an identifying name, do not belong to associations, and did not go to diversity schools. Do not miss them.
    • For that reason, search without diversity filters as well and eyeball the results.

To learn to navigate the complex process, sign up for our new Program with three days of learning, practice, and support, and prove your skills by taking the Diversity Sourcing exam (CDSP).

Your upcoming 3-day course is perfectly timed for many employers aspiring to improve their diverse work culture.” – Bill Bargas, Owner, diversity.com

Recruiters, do not miss the Program – it has only a few spaces left.

We will wait for feedback and questions and will make it a regular class. Next time, we will present in November, most likely. Stay tuned!