Do you share LinkedIn's vision of creating economic opportunity for every member of the global workforce?
We're launching the LinkedIn Economic Graph Research program to encourage researchers, academics, and data-driven thinkers to propose how they would use data from LinkedIn to generate insights that may ultimately lead to new economic opportunities.
What research or analysis would you propose that has the potential to create economic opportunity using Economic Graph data?
As of June 15, 2017 the Economic Graph Research program call for proposals has closed. Thank you to all of the the researchers who have submitted their ideas.
Over the next several weeks, we will be reviewing research proposals to identify those that best meet the criteria listed below. If you have submitted a proposal, you or one of your colleagues will be contacted by a LinkedIn representative near the start of the upcoming U.S. academic year (sometime in August).
QUESTIONS ABOUT RESEARCH USING ECONOMIC GRAPH DATA?
If you have other questions about using Economic Graph data for research projects that fall outside of the scope of this program, if you would like updates about the EGR program, or if you would like to be notified about the next EGR call for proposals, you may contact the team at EconomicGraphResearchProposal@linkedin.com.
Economic Graph Research Submissions Requirements
What are the basic requirements to submit a proposal to the Economic Graph Research program?:
- To participate you must be 18 years of age.
- Teams of up to 5 individual participants are permitted.
- Proposals should be on behalf of universities, think tanks, non-governmental organizations or other non-profit entities. Proposals on behalf of for-profit organizations and governments will not be considered.
- Proposals must be submitted using the form provided by LinkedIn.
Research areas and topics, explained
Analytics is the discovery, interpretation, and communication of actionable insights from big data. At LinkedIn, our mission is to drive understanding and impactful decision-making through rigorous use of data. Our analytics is deeply tied to core modules of our ecosystem, including product, marketing, and sales. We are looking for research proposals that leverage big data analytics and data science to understand relationships in the economic graph, preferably in the following areas:
Relationship between career success and access to relationships;
Occupation skill set trends & predictions and how to get them;
Talent supplies and demand gap globally/by geo/country/industry;
Relationship between economics and professional mobility/talent migration.
LinkedIn aims to be the go-to source for economic research that creates opportunity for every potential member of the global workforce. Within the Economic Graph Research umbrella, we are interested in rigorously investigating economic and labor market phenomena.
We are particularly interested in proposals for measuring the relative importance of credentials vs. skills in determining labor market outcomes.
For Relevance we are interested in a variety of machine learning and predictive modeling problems. They are the fundamental building blocks to drive search, discovery and recommendation across the LinkedIn ecosystem. We are looking for research proposals in this broad context, with preferences given to the following areas:
Large-scale machine learning, including large-scale methods for massive graphs/networks, fast online computations of models, deep learning of knowledge graphs, etc.
Personalized machine learning, such as content recommendation for each member, job recommendations for each job seeker, member intention modeling, etc.
Reinforcement learning, such as developing conversational interfaces, real-time exploration/exploitation, etc.
Crowdsourcing for social networks, for social applications that are highly personalized (feed ranking, link recommendation, etc.).
Causal inference, for root-cause analysis and real-time problem triaging.
Mining semi-structured & unstructured data, for member information standardization, content understanding and recommendation, etc.
Mining time-series & spatial data, for trend analysis, member life-cycle modeling, etc.
Security & privacy in machine learning, such as detecting and removing fake accounts, preventing member data breach, etc.
What is the selection process?
LinkedIn’s EGR team will review submitted proposals and notify selected proposals within 3 months of the end of the submission period.
We might ask for supplemental materials such as an endorsement letter from the higher-level management of the organization.
Proposals will be evaluated on a combination of three factors:
Novelty: the thoughtfulness and originality of the entry, including its unique approach to taking advantage of data from the Economic Graph.
Impact: the potential benefits to the region, country and the world, as well as the extensibility of the proposal.
Feasibility: the practicality of the submission, measuring the likelihood it can be researched and implemented within a reasonable time period and the types of data from LinkedIn that will be necessary for the proposed research.
Before your final selection, your organization will be required to enter into a contract with LinkedIn that covers your access and use of data from LinkedIn, confidentiality, and intellectual property. We will provide you with a copy of this agreement before final acceptance our your proposal into the LinkedIn Economic Graph Research program.
If you are selected, how will research be conducted?
If you are selected to participate, you or your teammates must be willing to learn basic big data languages and tools (e.g. Hadoop, Pig/Hive, Spark, Scala) in order to gain access to data from LinkedIn. It is better if you already have these skills when you submit your proposal.
The team will have monthly review meeting with EGR committee to share updates and results, allowing for better chance of success.
At the end of research period, the team has a chance to visit LinkedIn headquarters campus to present the research work.
Your access to data from LinkedIn will be limited. You will only be able to access data from LinkedIn for the purposes of conducting your proposed research. The data from LinkedIn will be made available in a separate, secure “sandbox” environment on LinkedIn hardware.