Section: Overview
Key publications
Research funding
Supervising & teaching

Key details

Areas of expertise

  • Data analytics for business applications
  • Social media analytics
  • Machine learning and AI

Available to supervise research students

Available for media queries

About Maria Prokofieva

Dr Maria Prokofieva is a senior lecturer at Victoria University Business School. She has also held academic positions at La Trobe University and Monash University, Australia.

She has a Bachelor in IT and Graduate Certificate in Accounting and her PhD is in the area of Business Information Systems (Russia).

With background in IT and Business. Maria is a quantitative researcher. Her areas of interest are:

  • data analytics
  • social media analytics
  • business intelligence and machine learning.

She is also interested in investigating in business application of data analytics and machine learning/AI.

Her outstanding work has appeared in top-tier outlets of the field, such as:

  • Journal of the Association for Information Systems
  • Journal of Information Systems
  • Australasian Journal of Educational Technology
  • Issues in Accounting Education.

Maria is passionate about using R/Python in academic research and everyday life. 

She is a member of:

  • Women Who Code
  • R Ladies Melbourne
  • Melbourne Users of R Network (MelbURN)
  • Melbourne Women in Machine Learning
  • Data Science and Data Science Melbourne.

She is also a Women in Data Science (WiDS) Ambassador.


  • Bachelor (IT), Russia
  • Bachelor (Education), Russia
  • Master (IT), Russia
  • PhD (IS/Business), Russia
  • GradCert (Accounting), La Trobe, Australia

Key publications

Year Citation
2023 Zarate, D., Ball, M., Prokofieva, M., Kostakos, V., & Stavropoulos, V. (231201). Identifying self-disclosed anxiety on Twitter: A natural language processing approach. Psychiatry Research, 330

doi: 10.1016/j.psychres.2023.115579

2023 Prokofieva, M., Zarate, D., Parker, A., Palikara, O., & Stavropoulos, V. (231201). Exploratory structural equation modeling: a streamlined step by step approach using the R Project software. BMC Psychiatry, 23(1),

doi: 10.1186/s12888-023-05028-9

2023 Stavropoulos, V., Zarate, D., Prokofieva, M., Van, de., Karimi, L., Gorman, Alesi., Richards, M., Bennet, S., & Griffiths, M. D. (231101). Deep learning(s) in gaming disorder through the user-avatar bond: A longitudinal study using machine learning.. Journal of behavioral addictions,

doi: 10.1556/2006.2023.00062

2023 Prokofieva, M. (230601). Integrating data analytics in teaching audit with machine learning and artificial intelligence. Education and Information Technologies, 28(6), (7317-7353).

doi: 10.1007/s10639-022-11474-x

2023 Alharasis, E. E., Prokofieva, M., & Clark, C. (230320). The moderating impact of auditor industry specialisation on the relationship between fair value disclosure and audit fees: empirical evidence from Jordan. Asian Review of Accounting, 31(2), (227-255).

doi: 10.1108/ARA-03-2022-0050

2023 Zarate, D., Tran, T. TD., Rehm, I., Prokofieva, M., & Stavropoulos, V. (230101). Measuring problematic sexual behaviour: an item response theory examination of the Bergen-Yale sex addiction scale. Clinical Psychologist, 27(3), (328-342).

doi: 10.1080/13284207.2023.2221781

2023 Zarate, D., Dorman, G., Prokofieva, M., Morda, R., & Stavropoulos, V. (230101). Online Behavioral Addictions: Longitudinal Network Analysis and Invariance Across Men and Women. Technology, Mind, and Behavior, 4(1),

doi: 10.1037/tmb0000105

2022 Ghahramani, A., de, Courten., & Prokofieva, M. (221201). The potential of social media in health promotion beyond creating awareness: an integrative review . BMC Public Health, 22(1),

doi: 10.1186/s12889-022-14885-0

2022 Stavropoulos, V., Footitt, T., Zarate, D., Prokofieva, M., & Griffiths, M. D. (221201). The Online Flow Questionnaire: An Item Response Theory Examination. Cyberpsychology, Behavior, and Social Networking, 25(12), (793-801).

doi: 10.1089/cyber.2022.0031

2022 Stavropoulos, V., Monger, K., Zarate, D., Prokofieva, M., & Schivinski, B. (221201). Online Gambling Disorder Questionnaire (OGD-Q): An item r esponse theory examination. Addictive Behaviors Reports, 16

doi: 10.1016/j.abrep.2022.100449

Research funding for the past 5 years

Please note:

  • Funding is ordered by the year the project commenced and may continue over several years.
  • Funding amounts for contact research are not disclosed to maintain commercial confidentiality.
  • The order of investigators is not indicative of the role they played in the research project.

Impact of student cultural background on NAPLAN performance
From: Melbourne Archdiocese Catholic Schools Ltd
Other investigators: Dr Shuyan Huo, Mr Andrew Wade, Dr Melissa Tham
For period: 2022-2023
Not disclosed

Data Analytics in External Auditing
From: CPA Australia
For period: 2020-2020

Supervision of research students at VU

Available to supervise research students

Available for media queries

Currently supervised research students at VU

No. of students Study level Role
2 PhD Integrated Principal supervisor
2 PhD Integrated Associate supervisor
1 Master of Research Associate supervisor

Currently supervised research students at VU

Students & level Role
PhD Integrated (2) Principal supervisor
PhD Integrated (2) Associate supervisor
Master of Research (1) Associate supervisor

Completed supervision of research students at VU

No. of students Study level Role
3 PhD Associate supervisor
2 Doctor of Business Administration Associate supervisor
1 PhD Integrated Associate supervisor

Completed supervision of research students at VU

Students & level Role
PhD (3) Associate supervisor
Doctor of Business Administration (2) Associate supervisor
PhD Integrated (1) Associate supervisor


Details of this Researcher's career are currently unavailable.