Forecasting managerial turnover through e-mail based social network analysis

• URL: http://arxiv.org/abs/2105.09208v1
• Date: Wed, 19 May 2021 15:39:55 GMT
• Title: Forecasting managerial turnover through e-mail based social network analysis
• Authors: P. A. Gloor, A. Fronzetti Colladon, F. Grippa, G. Giacomelli
• Abstract summary: We analyzed the communication behavior of 866 managers, out of which 111 left a large global service company. We compared differences in communication patterns by computing social network metrics. Results indicate that on average managers who quit had lower closeness centrality and less engaged conversations.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: In this study we propose a method based on e-mail social network analysis to compare the communication behavior of managers who voluntarily quit their job and managers who decide to stay. Collecting 18 months of e-mail, we analyzed the communication behavior of 866 managers, out of which 111 left a large global service company. We compared differences in communication patterns by computing social network metrics, such as betweenness and closeness centrality, and content analysis indicators, such as emotionality and complexity of the language used. To study the emergence of managers' disengagement, we made a distinction based on the period of e-mail data examined. We observed communications during months 5 and 4 before managers left, and found significant variations in both their network structure and use of language. Results indicate that on average managers who quit had lower closeness centrality and less engaged conversations. In addition, managers who chose to quit tended to shift their communication behavior starting from 5 months before leaving, by increasing their degree and closeness centrality, the complexity of their language, as well as their oscillations in betweenness centrality and the number of "nudges" they need to send to peers before getting an answer.

Related papers

• Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee Departures [7.151888974617969]
  We examine the effects of employee exits on socialization networks among the remaining coworkers. We find evidence of breakdown" in communication among the remaining coworkers. At the internal level, however, we find patterns suggesting individuals may end up better positioned in their networks after a network neighbor's departure.
  arXiv  Detail & Related papers  (2024-02-24T02:02:53Z)
• Over-communicate no more: Situated RL agents learn concise communication protocols [78.28898217947467]
  It is unclear how to design artificial agents that can learn to effectively and efficiently communicate with each other. Much research on communication emergence uses reinforcement learning (RL) We explore situated communication in a multi-step task, where the acting agent has to forgo an environmental action to communicate. We find that while all tested pressures can disincentivise over-communication, situated communication does it most effectively and, unlike the cost on effort, does not negatively impact emergence.
  arXiv  Detail & Related papers  (2022-11-02T21:08:14Z)
• From words to connections: Word use similarity as an honest signal conducive to employees' digital communication [0.0]
  We analyse the communication of close to 1600 employees, interacting on the intranet communication forum of a large company. We find that word use similarity is the main driver of interaction, much more than other language characteristics or similarity in network position. Our results suggest carefully choosing the language according to the target audience and have practical implications for both company managers and online community administrators.
  arXiv  Detail & Related papers  (2021-11-11T10:32:33Z)
• Interpretation of Emergent Communication in Heterogeneous Collaborative Embodied Agents [83.52684405389445]
  We introduce the collaborative multi-object navigation task CoMON. In this task, an oracle agent has detailed environment information in the form of a map. It communicates with a navigator agent that perceives the environment visually and is tasked to find a sequence of goals. We show that the emergent communication can be grounded to the agent observations and the spatial structure of the 3D environment.
  arXiv  Detail & Related papers  (2021-10-12T06:56:11Z)
• RelaySum for Decentralized Deep Learning on Heterogeneous Data [71.36228931225362]
  In decentralized machine learning, workers compute model updates on their local data. Because the workers only communicate with few neighbors without central coordination, these updates propagate progressively over the network. This paradigm enables distributed training on networks without all-to-all connectivity, helping to protect data privacy as well as to reduce the communication cost of distributed training in data centers.
  arXiv  Detail & Related papers  (2021-10-08T14:55:32Z)
• Few-shot Language Coordination by Modeling Theory of Mind [95.54446989205117]
  We study the task of few-shot $textitlanguage coordination$. We require the lead agent to coordinate with a $textitpopulation$ of agents with different linguistic abilities. This requires the ability to model the partner's beliefs, a vital component of human communication.
  arXiv  Detail & Related papers  (2021-07-12T19:26:11Z)
• Measuring the impact of spammers on e-mail and Twitter networks [0.0]
  This paper investigates if senders of large amounts of irrelevant or unsolicited information - commonly called "spammers" - distort the network structure of social networks. Two large social networks are analyzed, the first extracted from the Twitter discourse about a big telecommunication company, and the second obtained from three years of email communication of 200 managers working for a large multinational company. Results show that spammers do not significantly alter the structure of the information-carrying network, for most of the social indicators.
  arXiv  Detail & Related papers  (2021-05-21T10:13:11Z)
• The impact of virtual mirroring on customer satisfaction [0.0]
  We investigate the impact of a novel method called "virtual mirroring" to promote employee self-reflection and impact customer satisfaction. Our goal is to demonstrate that self-reflection can trigger a change in communication behaviors, which lead to increased customer satisfaction. We find that customer satisfaction is higher when employees are more responsive, use a simpler language, are embedded in less centralized communication networks, and show more stable leadership patterns.
  arXiv  Detail & Related papers  (2021-05-20T07:51:13Z)
• Robustness and stability of enterprise intranet social networks: The impact of moderators [0.0]
  We analyzed more than 52,000 messages posted by approximately 12,000 employees. We removed the forum moderators, the spammers, the overly connected nodes and the nodes lying at the network periphery. Our findings can help online community managers to understand the role of moderators within intranet forums.
  arXiv  Detail & Related papers  (2021-05-19T13:43:03Z)
• A game-theoretic analysis of networked system control for common-pool resource management using multi-agent reinforcement learning [54.55119659523629]
  Multi-agent reinforcement learning has recently shown great promise as an approach to networked system control. Common-pool resources include arable land, fresh water, wetlands, wildlife, fish stock, forests and the atmosphere.
  arXiv  Detail & Related papers  (2020-10-15T14:12:26Z)
• Communication Efficient Distributed Learning with Censored, Quantized, and Generalized Group ADMM [52.12831959365598]
  We propose a communication-efficiently decentralized machine learning framework that solves a consensus optimization problem defined over a network of inter-connected workers. The proposed algorithm, Censored and Quantized Generalized GADMM, leverages the worker grouping and decentralized learning ideas of Group Alternating Direction Method of Multipliers (GADMM) Numerical simulations corroborate that CQ-GGADMM exhibits higher communication efficiency in terms of the number of communication rounds and transmit energy consumption without compromising the accuracy and convergence speed.
  arXiv  Detail & Related papers  (2020-09-14T14:18:19Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.