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Inferring social signals to identify a passive candidates

IP.com Disclosure Number: IPCOM000243751D
Publication Date: 2015-Oct-16
Document File: 3 page(s) / 118K

Publishing Venue

The IP.com Prior Art Database

Abstract

Companies are currently ramping up their direct hire efforts on a global basis, using LinkedIn and other online tools to identify and approach suitable candidates. Some of these will be actively looking for a job, but most will be what we refer to as passive talent. This isn’t about suitability, we assume these candidates can do the job, this is a matter of seeing who will actually go through with shifting jobs. It is important to understand the right set of such candidates in order to have successful Recruitment. o Recruiting the social way via social Networks has gained significant momentum o Even more important than just identifying is to understand whether the candidate is ready for applying, or whether the candidate is looking for an alternate opportunity– a term referring to this is called “Opportunity Ready Candidates” – These kinds of talent pool is called passive talent. An added integral problem is to understand how the job opportunities would influence the candidates decisions to take up the opportunity or otherwise.

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Inferring social signals to identify a passive candidates

Technical Problem:
 In a social setting/media such as LinkedIn how to under the signals that different actions are associated it, and convert them into a score for determining opportunity readiness.

     o Two fundamental problems.
 What are the signals to be trapped?


o How do compute the score through the signals?


o What and how do external factors affect those signals?

Passive candidate characteristics

 Passive candidates are generally characterized by the following:
o They are Top talent in an organization
o Well connected in professional community.
o Impact full projects
o Need for analyzing the following factors for existing passive candidates:

Salary/compensation

       
Position in an organization
Impact in projects
Technical strengths
o Derive patterns from these to understand the characteristics of passive candidates.
o Temporal aspects since a person passive now -> perhaps might become active or had been active in the past.

Parameters to track

How does a candidate exhibit that he is interested in a specific shift. What factors indicate that the person might be interested in a shift?


o Analysis of his previous employment records

Frequent shifts perhaps indicate an expectation from the job. Some parameters that can be identified are
Salary
Position
Nature of the work (determined by the skills required).


o Analysis of the nature of the jobs he visited while searching for an employment and what he accepted.

Extract the features from the job's he has visited while taking up an employment.


 Salary


 Position


 Skills required in the job


 Roles required in the job

 Responsibilities in the job

These are all information that is tractable.

System Overview

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Approach

Step 1: Collecting complete data from the social media of a logged-in user.

Step 2: Building the signals repository from HR learning patterns - analyze previous candidates reached and the time at which they applied and relationship to their social behavior.

Step 3: For each social behavior/signal

store the mapping to the attributes that marked the change.

Step 4: For each candidate observe these attributes through time-series analysis.

Step 5: Observe signals for each candidate.

Step 6: If signal shows the patterns in repository, mark the candidates.

Step 7: Flag to recruiter that the candidate is "Opportunity Ready"

Highlights of this proposal

A system that can automatically identify candidates suitable for the job description, when the candidate is not explicitly applying for the position or is not actively looking for the positions. Such candidates are generally called Passive Candidate...