research-article

Detecting Job Promotion in Information Workers Using Mobile Sensing

Authors:

Shayan Mirjafari,

Gonzalo J. Martinez,

Aaron Striegel,

Andrew T. CampbellAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 4, Issue 3

Article No.: 113, Pages 1 - 28

https://doi.org/10.1145/3414118

Published: 04 September 2020 Publication History

Abstract

Most people desire promotions in the workplace. Typically, rising through the ranks comes with increased demands, better salary and higher status among peers. However, promoted workers have to deal with new challenges, such as, adjusting to new roles and responsibilities, which can in turn impact their physical and mental wellbeing. In this year long study, we use mobile sensing to track physiological and behavioral patterns of N=141 information workers who are promoted. We show that the workers experience a change in their physiological and behavioral patterns after promotion captured by passive sensing from phones, wearables and Bluetooth beacons. Furthermore, we use a random convolutions based approach to extract patterns from multivariate time series signals and evaluate the performance of different models to classify a worker's mobile sensing data as belonging to a promoted or non-promoted period with an AUC of 0.72. As a result, we report for the first time that mobile sensing can detect job promotion events by modeling physiological and behavioral changes of information workers in an objective manner.

References

[1]

Vernon L. Allen and Evert van de Vliert (Eds.). 1984. Role Transitions. Springer US. https://doi.org/10.1007/978-1-4613-2697-7

[2]

Samaneh Aminikhanghahi and Diane J. Cook. 2016. A survey of methods for time series change point detection. Knowledge and Information Systems 51, 2 (Sept. 2016), 339--367. https://doi.org/10.1007/s10115-016-0987-z

[3]

Michael Anderson and Michael Marmot. 2011. The Effects of Promotions on Heart Disease: Evidence from Whitehall. The Economic Journal 122, 561 (Oct. 2011), 555--589. https://doi.org/10.1111/j.1468-0297.2011.02472.x

[4]

Thereza Balliester, Adam Elsheikhi, et al. 2018. The future of work: A literature review. (2018).

[5]

K. Barton and R. B. Cattell. 1972. Personality factors related to job promotion and turnover. Journal of Counseling Psychology 19, 5 (1972), 430--435. https://doi.org/10.1037/h0033250

[6]

Yoav Benjamini and Yosef Hochberg. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological) 57, 1 (1995), 289--300.

[7]

Justin M Berg, Adam M Grant, and Victoria Johnson. 2010. When callings are calling: Crafting work and leisure in pursuit of unanswered occupational callings. Organization science 21, 5 (2010), 973--994.

[8]

Erik Berntson, Linda Wallin, and Annika Härenstam. 2012. Typical Situations for Managers in the Swedish Public Sector: Cluster Analysis of Working Conditions Using the Job Demands-Resources Model. International Public Management Journal 15, 1 (Jan. 2012), 100--130. https://doi.org/10.1080/10967494.2012.684026

[9]

Walter C Borman and SM Motowidlo. 1993. Expanding the criterion domain to include elements of contextual performance. (1993).

[10]

Christopher J. Boyce and Andrew J. Oswald. 2011. Do people become healthier after being promoted? Health Economics 21, 5 (April 2011), 580--596. https://doi.org/10.1002/hec.1734

[11]

Veerle Brenninkmeijer and Marleen Hekkert-Koning. 2015. To craft or not to craft. Career Development International 20, 2 (May 2015), 147--162. https://doi.org/10.1108/cdi-12-2014-0162

[12]

Jeanne M Brett. 1982. Job transfer and well-being. Journal of Applied Psychology 67, 4 (1982), 450.

[13]

Luca Canzian and Mirco Musolesi. 2015. Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis. In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing. 1293--1304.

Digital Library

[14]

Jose M Cortina and Joseph N Luchman. 2012. Personnel selection and employee performance. Handbook of Psychology, Second Edition 12 (2012).

[15]

Annet H. de Lange, Hans De Witte, and Guy Notelaers. 2008. Should I stay or should I go? Examining longitudinal relations among job resources and work engagement for stayers versus movers. Work & Stress 22, 3 (July 2008), 201--223. https://doi.org/10.1080/02678370802390132

[16]

Angus Dempster, François Petitjean, and Geoffrey I. Webb. 2020. ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge Discovery (July 2020). https://doi.org/10.1007/s10618-020-00701-z

[17]

Fabrizio D'Ovidio, Angelo d'Errico, Cecilia Scarinzi, and Giuseppe Costa. 2015. Increased incidence of coronary heart disease associated with "double burden" in a cohort of Italian women. Social Science & Medicine 135 (June 2015), 40--46. https://doi.org/10.1016/j.socscimed.2015.04.015

[18]

Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar, and Pierre-Alain Muller. 2019. Deep learning for time series classification: a review. Data Mining and Knowledge Discovery 33, 4 (March 2019), 917--963. https://doi.org/10.1007/s10618-019-00619-1

Digital Library

[19]

Hassan Ismail Fawaz, Benjamin Lucas, Germain Forestier, Charlotte Pelletier, Daniel F Schmidt, Jonathan Weber, Geoffrey I Webb, Lhassane Idoumghar, Pierre-Alain Muller, and François Petitjean. 2019. InceptionTime: Finding AlexNet for Time Series Classification. arXiv preprint arXiv:1909.04939 (2019).

[20]

FJ Ferri, Pavel Pudil, Mohamad Hatef, and Josef Kittler. 1994. Comparative study of techniques for large-scale feature selection. In Machine Intelligence and Pattern Recognition. Vol. 16. Elsevier, 403--413.

[21]

Jane Elizabeth Ferrie, Martin John Shipley, Stephen Alfred Stansfeld, and Michael Gideon Marmot. 2002. Effects of chronic job insecurity and change in job security on self reported health, minor psychiatric morbidity, physiological measures, and health related behaviours in British civil servants: the Whitehall II study. Journal of Epidemiology & Community Health 56, 6 (2002), 450--454.

[22]

Gary Fields. 2002. Predicting Potential For Promotion: How The Data In Human Resource Information Systems Can Be Used To Help Organizations Gain Competitive Advantage. CAHRS Working Paper Series (01 2002).

[23]

Marco Francesconi. 2001. Determinants and consequences of promotions in Britain. Oxford Bulletin of Economics and statistics 63, 3 (2001), 279--279.

[24]

Michael Frese. 1984. Transitions in Jobs, Occupational Socialization and Strain. In Role Transitions. Springer US, 239--252. https://doi.org/10.1007/978-1-4613-2697-7_17

[25]

Piotr Fryzlewicz. 2014. Wild binary segmentation for multiple change-point detection. The Annals of Statistics 42, 6 (Dec. 2014), 2243--2281. https://doi.org/10.1214/14-aos1245

[26]

Ross B Girshick, Jeff Donahue, Trevor Darrell, and Jitendra Malik. 2013. Rich feature hierarchies for accurate object detection and semantic segmentation. CoRR abs/1311.2524 (2013). arXiv preprint arXiv:1311.2524 (2013).

[27]

Fred H. Goldner. 1970. Success Vs. Failure: Prior Managerial Perspectives. Industrial Relations 9, 4 (Oct. 1970), 453--474. https://doi.org/10.1111/j.1468-232x.1970.tb00527.x

[28]

Ian Goodfellow, Yoshua Bengio, and Aaron Courville. 2016. Deep Learning. MIT Press. http://www.deeplearningbook.org.

Digital Library

[29]

Joan M Griffin, Rebecca Fuhrer, Stephen A Stansfeld, and Michael Marmot. 2002. The importance of low control at work and home on depression and anxiety: do these effects vary by gender and social class? Social science & medicine 54, 5 (2002), 783--798.

[30]

Mark A Griffin, Andrew Neal, and Sharon K Parker. 2007. A new model of work role performance: Positive behavior in uncertain and interdependent contexts. Academy of management journal 50, 2 (2007), 327--347.

[31]

Madeline E Heilman. 2001. Description and prescription: How gender stereotypes prevent women's ascent up the organizational ladder. Journal of social issues 57, 4 (2001), 657--674.

[32]

Yu Huang, Haoyi Xiong, Kevin Leach, Yuyan Zhang, Philip Chow, Karl Fua, Bethany A Teachman, and Laura E Barnes. 2016. Assessing social anxiety using GPS trajectories and point-of-interest data. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 898--903.

Digital Library

[33]

Jeremy F Huckins, Alex W DaSilva, Weichen Wang, Elin Hedlund, Courtney Rogers, Subigya K Nepal, Jialing Wu, Mikio Obuchi, Eilis I Murphy, Meghan L Meyer, et al. 2020. Mental Health and Behavior of College Students During the Early Phases of the COVID-19 Pandemic: Longitudinal Smartphone and Ecological Momentary Assessment Study. Journal of medical Internet research 22, 6 (2020), e20185.

[34]

Kevin Jarrett, Koray Kavukcuoglu, Marc'Aurelio Ranzato, and Yann LeCun. 2009. What is the best multi-stage architecture for object recognition?. In 2009 IEEE 12th international conference on computer vision. IEEE, 2146--2153.

[35]

Abelino Jiménez and Bhiksha Raj. 2019. Time signal classification using random convolutional features. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 3592--3596.

[36]

David W. Johnston and Wang-Sheng Lee. 2013. Extra Status and Extra Stress: Are Promotions Good for Us? ILR Review 66, 1 (Jan. 2013), 32--54. https://doi.org/10.1177/001979391306600102

[37]

Timothy A Judge and Shinichiro Watanabe. 1994. Individual differences in the nature of the relationship between job and life satisfaction. Journal of occupational and organizational psychology 67, 2 (1994), 101--107.

[38]

Robert A Karasek Jr. 1979. Job demands, job decision latitude, and mental strain: Implications for job redesign. Administrative science quarterly (1979), 285--308.

[39]

Hye-Geum Kim, Eun-Jin Cheon, Dai-Seg Bai, Young Hwan Lee, and Bon-Hoon Koo. 2018. Stress and Heart Rate Variability: A Meta-Analysis and Review of the Literature. Psychiatry Investigation 15, 3 (March 2018), 235--245. https://doi.org/10.30773/pi.2017.08.17

[40]

Michael W. Kramer and Timothy L. Noland. 1999. Communication during job promotions: A case of ongoing assimilation. Journal of Applied Communication Research 27, 4 (Nov. 1999), 335--355. https://doi.org/10.1080/00909889909365544

[41]

Edgar Krau. 1983. The attitudes toward work in career transitions. Journal of Vocational Behavior 23, 3 (1983), 270--285.

[42]

Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. Nature 521, 7553 (May 2015), 436--444. https://doi.org/10.1038/nature14539

[43]

Nira Liberman, Lorraine Chen Idson, Christopher J Camacho, and E Tory Higgins. 1999. Promotion and prevention choices between stability and change. Journal of personality and social psychology 77, 6 (1999), 1135.

[44]

Yuxi Long, Jiamin Liu, Ming Fang, Tao Wang, and Wei Jiang. 2018. Prediction of Employee Promotion Based on Personal Basic Features and Post Features. In Proceedings of the International Conference on Data Processing and Applications - ICDPA 2018. ACM Press. https://doi.org/10.1145/3224207.3224210

Digital Library

[45]

Garmin Ltd. 2019. Activity Tracking. https://buy.garmin.com/en-US/US/p/567813. [Online Access].

[46]

M. Malik, J. T. Bigger, A. J. Camm, R. E. Kleiger, A. Malliani, A. J. Moss, and P. J. Schwartz. 1996. Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. European Heart Journal 17, 3 (March 1996), 354--381. https://doi.org/10.1093/oxfordjournals.eurheartj.a014868

[47]

H. B. Mann and D. R. Whitney. 1947. On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other. The Annals of Mathematical Statistics 18, 1 (March 1947), 50--60. https://doi.org/10.1214/aoms/1177730491

[48]

Gonzalo J Martinez, Stephen Mattingly, Shayan Mirjafari, Subigya Nepal, Andrew Campbell, Anind Dey, and Aaron D Striegel. 2020. On the Quality of Real-world Wearable Data in a Longitudinal Study of Information Workers. In WristSense 2020: 6th Workshop on Sensing Systems and Applications using Wrist Worn Smart Devices (WristSense 2020). Austin, USA.

[49]

Gonzalo J. Martinez, Stephen Mattingly, Jessica Young, Louis Faust, Anind Dey, Andrew Campbell, Munmun Choudhury, Shayan Mirjafari, Subigya Nepal, Pablo Robles-Granda, Koustuv Saha, and Aaron D. Striegel. 2020. Improved Sleep Detection Through the Fusion of Phone Agent and Wearable Data Streams. In WristSense 2020: 6th Workshop on Sensing Systems and Applications using Wrist Worn Smart Devices (WristSense 2020). Austin, USA.

[50]

B.W. Matthews. 1975. Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA) - Protein Structure 405, 2 (Oct. 1975), 442--451. https://doi.org/10.1016/0005-2795(75)90109-9

[51]

Stephen M Mattingly, Julie M Gregg, Pino Audia, Ayse Elvan Bayraktaroglu, Andrew T Campbell, Nitesh V Chawla, Vedant Das Swain, Munmun De Choudhury, Sidney K D'Mello, Anind K Dey, et al. 2019. The Tesserae project: Large-scale, longitudinal, in situ, multimodal sensing of information workers. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems. 1--8.

Digital Library

[52]

Shayan Mirjafari, Anind K. Dey, Sidney K. D'Mello, Ge Gao, Julie M. Gregg, Krithika Jagannath, Kaifeng Jiang, Suwen Lin, Qiang Liu, Gloria Mark, Gonzalo J. Martinez, Kizito Masaba, Stephen M. Mattingly, Edward Moskal, Raghu Mulukutla, Subigya Nepal, Kari Nies, Manikanta D. Reddy, Pablo Robles-Granda, Koustuv Saha, Anusha Sirigiri, Aaron Striegel, Ted Grover, Weichen Wang, Pino Audia, Andrew T. Campbell, Nitesh V. Chawla, Vedant Das Swain, and Munmun De Choudhury. 2019. Differentiating Higher and Lower Job Performers in the Workplace Using Mobile Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 2 (June 2019), 1--24. https://doi.org/10.1145/3328908

Digital Library

[53]

Bjarke Mønsted, Anders Mollgaard, and Joachim Mathiesen. 2018. Phone-based metric as a predictor for basic personality traits. Journal of Research in Personality 74 (June 2018), 16--22. https://doi.org/10.1016/j.jrp.2017.12.004

[54]

Skanda Muralidhar, Marianne Schmid Mast, and Daniel Gatica-Perez. 2018. A Tale of Two Interactions. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 3 (Sept. 2018), 1--24. https://doi.org/10.1145/3264939

Digital Library

[55]

Nigel Nicholson. 1984. A theory of work role transitions. Administrative science quarterly (1984), 172--191.

[56]

Anna Nyberg, Linda L. Magnusson Hanson, Constanze Leineweber, and Gunn Johansson. 2015. Do Predictors of Career Success Differ between Swedish Women and Men? Data from the Swedish Longitudinal Occupational Survey of Health (SLOSH). PLOS ONE 10, 10 (Oct. 2015), e0140516. https://doi.org/10.1371/journal.pone.0140516

[57]

Anna Nyberg, Constanze Leineweber, and Linda Magnusson Hanson. 2015. Gender differences in psychosocial work factors, work-personal life interface, and well-being among Swedish managers and non-managers. International Archives of Occupational and Environmental Health 88, 8 (March 2015), 1149--1164. https://doi.org/10.1007/s00420-015-1043-0

[58]

Anna Nyberg, Paraskevi Peristera, Hugo Westerlund, Gunn Johansson, and Linda L Magnusson Hanson. 2016. Does job promotion affect men's and women's health differently? Dynamic panel models with fixed effects. International Journal of Epidemiology (Dec. 2016), dyw310. https://doi.org/10.1093/ije/dyw310

[59]

Mikio Obuchi, Jeremy F. Huckins, Weichen Wang, Alex daSilva, Courtney Rogers, Eilis Murphy, Elin Hedlund, Paul Holtzheimer, Shayan Mirjafari, and Andrew Campbell. 2020. Predicting Brain Functional Connectivity Using Mobile Sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 4, 1 (March 2020), 1--22. https://doi.org/10.1145/3381001

Digital Library

[60]

Maxime Oquab, Léon Bottou, Ivan Laptev, and Josef Sivic. 2015. Is object localization for free?-weakly-supervised learning with convolutional neural networks. In Proceedings of the IEEE conference on computer vision and pattern recognition. 685--694.

[61]

Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32, H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, and R. Garnett (Eds.). Curran Associates, Inc., 8024--8035. http://papers.neurips.cc/paper/9015-pytorch-an-imperative-style-high-performance-deep-learning-library.pdf

Digital Library

[62]

Ali Rahimi and Benjamin Recht. 2008. Random features for large-scale kernel machines. In Advances in neural information processing systems. 1177--1184.

[63]

Abdul Razak, Sarpan Sarpan, Ramlan Ramlan, et al. 2018. Influence of promotion and job satisfaction on employee performance. Journal of Accounting, Business and Finance Research 3, 1 (2018), 18--27.

[64]

Reeshad s. Dalal, Holly Lam, Howard M. Weiss, Eric R. Welch, and Charles L. Hulin. 2009. A Within-Person Approach to Work Behavior and Performance: Concurrent and Lagged Citizenship-Counterproductivity Associations, and Dynamic Relationships with Affect and Overall Job Performance. Academy of Management Journal 52, 5 (Oct. 2009), 1051--1066. https://doi.org/10.5465/amj.2009.44636148

[65]

Paul R Sackett. 2002. The structure of counterproductive work behaviors: Dimensionality and relationships with facets of job performance. International journal of selection and assessment 10, 1-2 (2002), 5--11.

[66]

Sohrab Saeb, Emily G Lattie, Konrad P Kording, and David C Mohr. 2017. Mobile phone detection of semantic location and its relationship to depression and anxiety. JMIR mHealth and uHealth 5, 8 (2017), e112.

[67]

Saharuddin and Sulaiman. 2016. The Effect Of Promotion And Compensation Toward Working Productivity Through Job Satisfaction And Working Motivation Of Employees In The Department Of Water And Mineral Resources Energy North Aceh.

[68]

Andrew Saxe, Pang Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, and Andrew Ng. 2011. On Random Weights and Unsupervised Feature Learning. Proceedings of the 28th International Conference on Machine Learning, 1089--1096.

[69]

Emiliano Sironi. 2019. Job satisfaction as a determinant of employees' optimal well-being in an instrumental variable approach. Quality & Quantity 53, 4 (Jan. 2019), 1721--1742. https://doi.org/10.1007/s11135-019-00835-3

[70]

M. Sornam, Kavitha Muthusubash, and V. Vanitha. 2017. A Survey on Image Classification and Activity Recognition using Deep Convolutional Neural Network Architecture. In 2017 Ninth International Conference on Advanced Computing (ICoAC). IEEE. https://doi.org/10.1109/icoac.2017.8441512

[71]

Seymour Spilerman and Tormod Lunde. 1991. Features of Educational Attainment and Job Promotion Prospects. Amer. J. Sociology 97, 3 (Nov. 1991), 689--720. https://doi.org/10.1086/229817

[72]

Stephen Alfred Stansfeld, Hans Bosma, Harry Hemingway, and Michael G Marmot. 1998. Psychosocial work characteristics and social support as predictors of SF-36 health functioning: the Whitehall II study. Psychosomatic medicine 60, 3 (1998), 247--255.

[73]

Stephen A Stansfeld, Rebecca Fuhrer, Martin J Shipley, and Michael G Marmot. 1999. Work characteristics predict psychiatric disorder: prospective results from the Whitehall II Study. Occupational and environmental medicine 56, 5 (1999), 302--307.

[74]

Daniel J Stekhoven and Peter Bühlmann. 2012. MissForest---non-parametric missing value imputation for mixed-type data. Bioinformatics 28, 1 (2012), 112--118.

Digital Library

[75]

Vedant Das Swain, Koustuv Saha, Hemang Rajvanshy, Anusha Sirigiri, Julie M. Gregg, Suwen Lin, Gonzalo J. Martinez, Stephen M. Mattingly, Shayan Mirjafari, Raghu Mulukutla, Subigya Nepal, Kari Nies, Manikanta D. Reddy, Pablo Robles-Granda, Andrew T. Campbell, Nitesh V. Chawla, Sidney D'Mello, Anind K. Dey, Kaifeng Jiang, Qiang Liu, Gloria Mark, Edward Moskal, Aaron Striegel, Louis Tay, Gregory D. Abowd, and Munmun De Choudhury. 2019. A Multisensor Person-Centered Approach to Understand the Role of Daily Activities in Job Performance with Organizational Personas. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3, 4 (Dec. 2019), 1--27. https://doi.org/10.1145/3369828

[76]

Firstbeat Technologies. 2014. Stress and Recovery Analysis Method Based on 24-hour Heart Rate Variability. https://assets.firstbeat.com/firstbeat/uploads/2015/10/Stress-and-recovery_white-paper_20145.pdf

[77]

Maria Tims and Arnold B. Bakker. 2010. Job crafting: Towards a new model of individual job redesign. SA Journal of Industrial Psychology 36, 2 (Dec. 2010). https://doi.org/10.4102/sajip.v36i2.841

[78]

Maria Tims, Arnold B Bakker, and Daantje Derks. 2012. Development and validation of the job crafting scale. Journal of vocational behavior 80, 1 (2012), 173--186.

[79]

Charles Truong, Laurent Oudre, and Nicolas Vayatis. 2019. Selective review of offline change point detection methods. Signal Processing (2019), 107299.

[80]

Ari Väänänen, May V. Kevin, Leena Ala-Mursula, Jaana Pentti, Mika Kivimäki, and Jussi Vahtera. 2005. The Double Burden of and Negative Spillover Between Paid and Domestic Work: Associations with Health Among Men and Women. Women & Health 40, 3 (April 2005), 1--18. https://doi.org/10.1300/j013v40n03_01

[81]

Rui Wang, Min SH Aung, Saeed Abdullah, Rachel Brian, Andrew T Campbell, Tanzeem Choudhury, Marta Hauser, John Kane, Michael Merrill, Emily A Scherer, et al. 2016. CrossCheck: toward passive sensing and detection of mental health changes in people with schizophrenia. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM, 886--897.

Digital Library

[82]

Rui Wang, Fanglin Chen, Zhenyu Chen, Tianxing Li, Gabriella Harari, Stefanie Tignor, Xia Zhou, Dror Ben-Zeev, and Andrew T Campbell. 2014. StudentLife: assessing mental health, academic performance and behavioral trends of college students using smartphones. In Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing. 3--14.

Digital Library

[83]

Rui Wang, Weichen Wang, Alex daSilva, Jeremy F Huckins, William M Kelley, Todd F Heatherton, and Andrew T Campbell. 2018. Tracking depression dynamics in college students using mobile phone and wearable sensing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, 1 (2018), 43.

Digital Library

[84]

Weichen Wang, Gabriella M. Harari, Rui Wang, Sandrine R. Müller, Shayan Mirjafari, Kizito Masaba, and Andrew T. Campbell. 2018. Sensing Behavioral Change over Time: Using Within-Person Variability Features from Mobile Sensing to Predict Personality Traits. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 3, Article 141 (Sept. 2018), 21 pages. https://doi.org/10.1145/3264951

[85]

Weichen Wang, Shayan Mirjafari, Gabriella Harari, Dror Ben-Zeev, Rachel Brian, Tanzeem Choudhury, Marta Hauser, John Kane, Kizito Masaba, Subigya Nepal, et al. 2020. Social Sensing: Assessing Social Functioning of Patients Living with Schizophrenia using Mobile Phone Sensing. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1--15.

Digital Library

[86]

Frank Wilcoxon. 1945. Individual Comparisons by Ranking Methods. Biometrics Bulletin 1, 6 (Dec. 1945), 80. https://doi.org/10.2307/3001968

[87]

Larry J Williams and Stella E Anderson. 1991. Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors. Journal of management 17, 3 (1991), 601--617.

[88]

David A Wise. 1975. Personal attributes, job performance, and probability of promotion. Econometrica: Journal of the Econometric Society (1975), 913--931.

[89]

Amy Wrzesniewski, Nicholas LoBuglio, Jane E Dutton, and Justin M Berg. 2013. Job crafting and cultivating positive meaning and identity in work. In Advances in positive organizational psychology. Emerald Group Publishing Limited.

[90]

Jason Yosinski, Jeff Clune, Yoshua Bengio, and Hod Lipson. 2014. How transferable are features in deep neural networks?. In Advances in neural information processing systems. 3320--3328.

[91]

Jia Yuan, Qian-Ming Zhang, Jian Gao, Linyan Zhang, Xue-Song Wan, Xiao-Jun Yu, and Tao Zhou. 2016. Promotion and resignation in employee networks. Physica A: Statistical Mechanics and its Applications 444 (Feb. 2016), 442--447. https://doi.org/10.1016/j.physa.2015.10.039

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Index Terms

Detecting Job Promotion in Information Workers Using Mobile Sensing
1. Human-centered computing
  1. Ubiquitous and mobile computing

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 4, Issue 3

September 2020

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DOI:10.1145/3422862

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Choi AOoi ALottridge D(2024)Digital Phenotyping for Stress, Anxiety, and Mild Depression: Systematic Literature ReviewJMIR mHealth and uHealth10.2196/4068912(e40689)Online publication date: 23-May-2024
https://doi.org/10.2196/40689
Gao NYu ZXu YYu CWang YSalim FShi YKostakos VKay JHoang T(2024)Leveraging Large Language Models for Generating Mobile Sensing Strategies in Human Behavior ModelingCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678423(729-735)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3678423
Naghizade EJi KTag BSalim FKostakos VKay JHoang T(2024)Inside Out or Not: Privacy Implications of Emotional DisclosureCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3677598(121-125)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3677598
Sahu NGupta SLone H(2024)Wearable Technology Insights: Unveiling Physiological Responses During Three Different Socially Anxious ActivitiesACM Journal on Computing and Sustainable Societies10.1145/36636712:2(1-23)Online publication date: 9-May-2024
https://dl.acm.org/doi/10.1145/3663671
Nepal SLiu WPillai AWang WVojdanovski VHuckins JRogers CMeyer MCampbell A(2024)Capturing the College ExperienceProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36435018:1(1-37)Online publication date: 6-Mar-2024
https://dl.acm.org/doi/10.1145/3643501
Nepal SHernandez JLewis RChaudhry AHouck BKnudsen ERojas RTankus BPrafullchandra HCzerwinski M(2024)Burnout in Cybersecurity Incident Responders: Exploring the Factors that Light the FireProceedings of the ACM on Human-Computer Interaction10.1145/36373048:CSCW1(1-35)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637304
Necaise AMejia CKider JShoss MAmon M(2024)Wearables for Well-Being: A Longitudinal in Situ Study of Smartwatches to Understand and Enhance Line-Level Housekeeping WorkInternational Journal of Human–Computer Interaction10.1080/10447318.2024.2313887(1-17)Online publication date: 15-Mar-2024
https://doi.org/10.1080/10447318.2024.2313887
Bouhsaien LAzmani ABenallou I(2024)A Combined AHP-TOPSIS Model for the Selection of Employees for PromotionSmart Applications and Data Analysis10.1007/978-3-031-77040-1_13(175-189)Online publication date: 24-Dec-2024
https://doi.org/10.1007/978-3-031-77040-1_13
Chowdhary SKawakami AGray MSuh JOlteanu ASaha K(2023)Can Workers Meaningfully Consent to Workplace Wellbeing Technologies?Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency10.1145/3593013.3594023(569-582)Online publication date: 12-Jun-2023
https://dl.acm.org/doi/10.1145/3593013.3594023
Nepal SHernandez JAmores Fernandez JBin Morshed MLewis RPrafullchandra HCzerwinski M(2023)Workplace Rhythm Variability and Emotional Distress in Information WorkersExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585626(1-8)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585626
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