research-article

Public Access

Career Transitions and Trajectories: A Case Study in Computing

Authors:

Maryam Davoodi,

Danai KoutraAuthors Info & Claims

KDD '18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Pages 675 - 684

https://doi.org/10.1145/3219819.3219863

Published: 19 July 2018 Publication History

Abstract

From artificial intelligence to network security to hardware design, it is well-known that computing research drives many important technological and societal advancements. However, less is known about the long-term career paths of the people behind these innovations. What do their careers reveal about the evolution of computing research? Which institutions were and are the most important in this field, and for what reasons? Can insights into computing career trajectories help predict employer retention?

In this paper we analyze several decades of post-PhD computing careers using a large new dataset rich with professional information, and propose a versatile career network model, R 3, that captures temporal career dynamics. With R 3 we track important organizations in computing research history, analyze career movement between industry, academia, and government, and build a powerful predictive model for individual career transitions. Our study, the first of its kind, is a starting point for understanding computing research careers, and may inform employer recruitment and retention mechanisms at a time when the demand for specialized computational expertise far exceeds supply.

References

[1]

Benjamin Balsmeier and Maikel Pellens . 2014. Who makes, who breaks: Which scientists stay in academe? Economics Letters, Vol. 122, 2 (2014), 229 -- 232.

[2]

Michael N. Bastedo and Nicholas A. Bowman . 2010. U.S. News & World Report College Rankings: Modeling Institutional Effects on Organizational Reputation. American Journal of Education Vol. 116, 2 (2010), 163--183.

[3]

Ivan Brugere, Brian Gallagher, and Tanya Y. Berger-Wolf . 2018. Network Structure Inference, A Survey: Motivations, Methods, and Applications. ACM Comput. Surv., Vol. 51, 2, Article bibinfoarticleno24 (April . 2018), bibinfonumpages39 pages.

Digital Library

[4]

Tanmoy Chakraborty and Subrata Nandi . 2018. Universal trajectories of scientific success. Knowledge and Information Systems Vol. 54, 2 (2018), 487--509.

Digital Library

[5]

Aaron Clauset, Samuel Arbesman, and Daniel B. Larremore . 2015. Systematic inequality and hierarchy in faculty hiring networks. Science Advances, Vol. 1, 1 (2015).

[6]

Aaron Clauset, Cosma Rohilla Shalizi, and M. E. J. Newman . 2009. Power-Law Distributions in Empirical Data. SIAM Rev. Vol. 51, 4 (2009), 661--703.

Digital Library

[7]

Tim Cross . 2016. After Moore's law. (2016). http://www.economist.com/technology-quarterly/2016-03--12/after-moores-law

[8]

T Deguchi, K Takahashi, H Takayasu, and M. Takayasu . 2014. Hubs and authorities in the world trade network using a weighted HITS algorithm. PLoS One, Vol. 9, 4 (2014).

[9]

Pierre Deville, Dashun Wang, Roberta Sinatra, Chaoming Song, Vincent D Blondel, and Albert-Laszlo Barabasi . 2014. Career on the Move: Geography, Stratification, and Scientific Impact. Scientific Reports Vol. 4 (2014).

[10]

Michalis Faloutsos, Petros Faloutsos, and Christos Faloutsos . 1999. On Power-law Relationships of the Internet Topology. SIGCOMM Comput. Commun. Rev. Vol. 29, 4 (Aug. . 1999), 251--262.

Digital Library

[11]

Robert G Ferguson . 2013. NASA's First A. The NASA History Series.

[12]

Joseph L. Fleiss . 1971. Measuring Nominal Scale Agreement Among Many Raters. Vol. 76 (11 . 1971), 378--.

[13]

Lise Getoor and Christopher P. Diehl . 2005. Link Mining: A Survey. SIGKDD Explor. Newsl., Vol. 7, 2 (Dec. . 2005), 3--12.

Digital Library

[14]

David F. Gleich . 2015. PageRank Beyond the Web. SIAM Rev. Vol. 57, 3 (2015), 321--363.

Digital Library

[15]

Jorge E Hirsch . 2005. An index to quantify an individual's scientific research output. Proceedings of the National academy of Sciences of the United States of America, Vol. 102, 46 (2005), 16569.

[16]

William Hoffmann and Hendrik Poorter . 2002. Avoiding Bias in Calculations of Relative Growth Rate. Vol. 90 (2002), 37--42.

[17]

Navneet Kapur, Nikita Lytkin, Bee-Chung Chen, Deepak Agarwal, and Igor Perisic . 2016. Ranking Universities Based on Career Outcomes of Graduates ACM KDD. 137--144.

Digital Library

[18]

Jon M. Kleinberg . 1999. Authoritative Sources in a Hyperlinked Environment. J. ACM, Vol. 46, 5 (Sept. . 1999), 604--632.

Digital Library

[19]

Danai Koutra, Paul N. Bennett, and Eric Horvitz . 2015. Events and Controversies: Influences of a Shocking News Event on Information Seeking WWW. International World Wide Web Conferences Steering Committee, 614--624.

Digital Library

[20]

Danai Koutra, Abhilash Dighe, Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis, Christos Faloutsos, and Jean Bolot . 2017. PNP: Fast Path Ensemble Method for Movie Design. KDD. ACM, 1527--1536.

Digital Library

[21]

Danai Koutra and Christos Faloutsos . 2017. Individual and Collective Graph Mining: Principles, Algorithms, and Applications. Synthesis Lectures on Data Mining and Knowledge Discovery, Vol. 9, 2 (2017), 1--206.

Digital Library

[22]

J Landis and Gary G. Koch . 1977. The Measurement Of Observer Agreement For Categorical Data. Vol. 33 (04 . 1977), 159--74.

[23]

Gautier Marti, Frank Nielsen, Mikolaj Binkowski, and Philippe Donnat . 2017. A review of two decades of correlations, hierarchies, networks and clustering in financial markets. (03 . 2017).

[24]

Cade Metz . 2017. Tech Giants Are Paying Huge Salaries for Scarce A.I. Talent. (2017). https://www.nytimes.com/2017/10/22/technology/artificial-intelligence-experts-salaries.html

[25]

Mark EJ Newman . 2009. The first-mover advantage in scientific publication. EPL (Europhysics Letters) Vol. 86, 6 (2009), 68001.

[26]

Richard J Oentaryo, Xiavier Jayaraj Ashok, Ee-Peng Lim, and Philis Kokoh Prasetyo . 2017. On Analyzing Job Hop Behavior and Talent Flow. In ICDM Data Science for Human Capital Management Workshop.

[27]

T. Safavi, C. Sripada, and D. Koutra . 2017. Scalable Hashing-Based Network Discovery. In ICDM. IEEE, 405--414.

[28]

Henry Sauermann and Michael Roach . 2012. Science PhD Career Preferences: Levels, Changes, and Advisor Encouragement. PLOS ONE, Vol. 7, 5 (05 . 2012), 1--9.

[29]

Hanghang Tong, Christos Faloutsos, and Jia-Yu Pan . 2006. Fast Random Walk with Restart and Its Applications ICDM. IEEE Computer Society, 613--622.

Digital Library

[30]

Vincent S. Tseng, Jia-Ching Ying, Che-Wei Huang, Yimin Kao, and Kuan-Ta Chen . 2015. FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection ACM KDD. 2157--2166.

Digital Library

[31]

Samuel F. Way, Allison C. Morgan, Aaron Clauset, and Daniel B. Larremore . 2017. The misleading narrative of the canonical faculty productivity trajectory. PNAS, Vol. 114, 44 (2017), E9216--E9223.

[32]

Huang Xu, Zhiwen Yu, Jingyuan Yang, Hui Xiong, and Hengshu Zhu . 2016 b. Talent Circle Detection in Job Transition Networks ACM KDD. 655--664.

Digital Library

[33]

Jian Xu, Thanuka L. Wickramarathne, and Nitesh V. Chawla . 2016 a. Representing higher-order dependencies in networks. Science Advances, Vol. 2, 5 (2016).

[34]

Ye Xu, Zang Li, Abhishek Gupta, Ahmet Bugdayci, and Anmol Bhasin . 2014. Modeling Professional Similarity by mining Professional Career Trajectories WWW.

Digital Library

[35]

Louis E. Yelle . 1979. The Learning Curve: Historical Review and Comprehensive Survey. Decision Sciences, Vol. 10, 2 (1979), 302--328.

Cited By

Liu JWang TYao FPedrycz WSong YHe R(2024)Assessing growth potential of careers with occupational mobility network and ensemble frameworkEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107306127:PAOnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.engappai.2023.107306
Shao ZYuan SJin YWang Y(2024)Scholar's career switch from academia to industry: Mining and analysis from AMinerBig Data Research10.1016/j.bdr.2024.100441(100441)Online publication date: Feb-2024
https://doi.org/10.1016/j.bdr.2024.100441
Saner PTratschin LLeder CRost K(2023)Introduction to the Special Issue: Digital Academia. Investigating Science and Higher Education in the Digital AgeSwiss Journal of Sociology10.2478/sjs-2023-002249:3(449-472)Online publication date: 31-Oct-2023
https://doi.org/10.2478/sjs-2023-0022
Show More Cited By

Index Terms

Career Transitions and Trajectories: A Case Study in Computing

Recommendations

Modeling professional similarity by mining professional career trajectories
KDD '14: Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining

For decades large corporations as well as labor placement services have maintained extensive yet static resume databanks. Online professional networks like LinkedIn have taken these resume databanks to a dynamic, constantly updated and massive scale ...
Career transition antecedents in the information technology area

The more organizations invest in information technology IT, the more the concern with IT personnel management has increased, namely the hiring, training and retaining of IT professionals needed to deal with such investments. In this context, two issues ...
Career Anchors and Employee Retention: An Empirical Study of Information Technology Industry in India

The success of Indian Information Technology IT industry is dependent on the ability of the organizations to retain the human potential. However, profound changes in the occupational environment have implications for an individual's career development ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

KDD '18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

July 2018

2925 pages

ISBN:9781450355520

DOI:10.1145/3219819

General Chairs:
Yike Guo
Imperial College London
,
Faisal Farooq
IBM

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 July 2018

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Conference

KDD '18

Sponsor:

KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 19 - 23, 2018

London, United Kingdom

Acceptance Rates

KDD '18 Paper Acceptance Rate 107 of 983 submissions, 11%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
776
Total Downloads

Downloads (Last 12 months)124
Downloads (Last 6 weeks)20

Reflects downloads up to 14 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Liu JWang TYao FPedrycz WSong YHe R(2024)Assessing growth potential of careers with occupational mobility network and ensemble frameworkEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.107306127:PAOnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.engappai.2023.107306
Shao ZYuan SJin YWang Y(2024)Scholar's career switch from academia to industry: Mining and analysis from AMinerBig Data Research10.1016/j.bdr.2024.100441(100441)Online publication date: Feb-2024
https://doi.org/10.1016/j.bdr.2024.100441
Saner PTratschin LLeder CRost K(2023)Introduction to the Special Issue: Digital Academia. Investigating Science and Higher Education in the Digital AgeSwiss Journal of Sociology10.2478/sjs-2023-002249:3(449-472)Online publication date: 31-Oct-2023
https://doi.org/10.2478/sjs-2023-0022
Ribes E(2021)What is the effect of labor displacement on management consultants?SN Business & Economics10.1007/s43546-021-00049-61:2Online publication date: 24-Feb-2021
https://doi.org/10.1007/s43546-021-00049-6
Cai XShang JJin ZLiu FQiang BXie WZhao L(2020)DBGE: Employee Turnover Prediction Based on Dynamic Bipartite Graph EmbeddingIEEE Access10.1109/ACCESS.2020.29655448(10390-10402)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2965544
Assunção RSouza RPrates M(2020)New Frontiers for Scan Statistics: Network, Trajectory, and Text DataHandbook of Scan Statistics10.1007/978-1-4614-8414-1_47-1(1-24)Online publication date: 4-May-2020
https://doi.org/10.1007/978-1-4614-8414-1_47-1
Saner P(2019)Envisioning Higher Education: How Imagining the Future Shapes the Implementation of a New Field in Higher EducationSwiss Journal of Sociology10.2478/sjs-2019-001745:3(359-381)Online publication date: 21-Nov-2019
https://doi.org/10.2478/sjs-2019-0017
Belth CKamran FTjandra DKoutra D(2019)When to remember where you came fromProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1145/3341161.3342911(222-225)Online publication date: 27-Aug-2019
https://dl.acm.org/doi/10.1145/3341161.3342911
He MShen DZhu YHe RWang TZhang Z(2019)Career Trajectory Prediction based on CNN2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)10.1109/SOLI48380.2019.8955009(22-26)Online publication date: Nov-2019
https://doi.org/10.1109/SOLI48380.2019.8955009

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents