research-article

Large-Scale Analysis of New Employee Network Dynamics

Authors:

Mengting WanAuthors Info & Claims

WWW '23: Proceedings of the ACM Web Conference 2023

Pages 2719 - 2730

https://doi.org/10.1145/3543507.3583400

Published: 30 April 2023 Publication History

Abstract

The COVID-19 pandemic has accelerated digital transformations across industries, but also introduced new challenges into workplaces, including the difficulties of effectively socializing with colleagues when working remotely. This challenge is exacerbated for new employees who need to develop workplace networks from the outset. In this paper, by analyzing a large-scale telemetry dataset of more than 10,000 Microsoft employees who joined the company in the first three months of 2022, we describe how new employees interact and telecommute with their colleagues during their “onboarding” period. Our results reveal that although new hires are gradually expanding networks over time, there still exists significant gaps between their network statistics and those of tenured employees even after the six-month onboarding phase. We also observe that heterogeneity exists among new employees in how their networks change over time, where employees whose job tasks do not necessarily require extensive and diverse connections could be at a disadvantaged position in this onboarding process. By investigating how web-based people recommendations in organizational knowledge base facilitate new employees naturally expand their networks, we also demonstrate the potential of web-based applications for addressing the aforementioned socialization challenges. Altogether, our findings provide insights on new employee network dynamics in remote and hybrid work environments, which may help guide organizational leaders and web application developers on quantifying and improving the socialization experiences of new employees in digital workplaces.

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Cited By

Yu YJiang JDhillon P(2024)Characterizing the Structure of Online Conversations Across RedditProceedings of the ACM on Human-Computer Interaction10.1145/36869138:CSCW2(1-23)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686913
Gamba DYu YYuan YSchoenebeck GRomero DChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee DeparturesProceedings of the ACM Web Conference 202410.1145/3589334.3645634(211-222)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645634
Charpignon MYuan YZhang DAmini FYang LJaffe SSuri S(2023)Navigating the new normal: Examining coattendance in a hybrid work environmentProceedings of the National Academy of Sciences10.1073/pnas.2310431120120:51Online publication date: 11-Dec-2023
https://doi.org/10.1073/pnas.2310431120

Index Terms

Large-Scale Analysis of New Employee Network Dynamics
1. Applied computing
  1. Law, social and behavioral sciences
    1. Sociology
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

WWW '23: Proceedings of the ACM Web Conference 2023

April 2023

4293 pages

ISBN:9781450394161

DOI:10.1145/3543507

Copyright © 2023 ACM.

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Published: 30 April 2023

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Cited By

Yu YJiang JDhillon P(2024)Characterizing the Structure of Online Conversations Across RedditProceedings of the ACM on Human-Computer Interaction10.1145/36869138:CSCW2(1-23)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686913
Gamba DYu YYuan YSchoenebeck GRomero DChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee DeparturesProceedings of the ACM Web Conference 202410.1145/3589334.3645634(211-222)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645634
Charpignon MYuan YZhang DAmini FYang LJaffe SSuri S(2023)Navigating the new normal: Examining coattendance in a hybrid work environmentProceedings of the National Academy of Sciences10.1073/pnas.2310431120120:51Online publication date: 11-Dec-2023
https://doi.org/10.1073/pnas.2310431120

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