Corps professoral

Maria OLMEDILLA FERNANDEZ

Professeur associé

eWOM communities, Text mining, Machine learning techniques, Online user behaviour, NLP, Intelligence artificielle

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Maria OLMEDILLA FERNANDEZ

Académie

Digitalisation

Centre de recherche

SKEMA Centre for Artificial Intelligence

Localisation

Paris

Discipline

Marketing
Formation
2017
Ph.D. in Strategic Management and International Business, University of Seville, Espagne
2014
MSc in Technology and Innovation Management, Brandenburg University of Technology Cottbus-Senftenberg (BTU), Allemagne
Expérience professionnelle
Positions académiques principales
Depuis 2019
Professeur associé, SKEMA Business School, France
2017 - 2019
Professeur assistant, École de management Léonard de Vinci, France
Autres affiliations académiques
Depuis 2023
Directeur Académique, SKEMA Business School, France
2014 - 2017
PhD Researcher, University of Seville, Espagne
Autres expériences professionnelles
2012 - 2015
Freelancer consultant, GRUPO AMETS GESTIÓN I+D+i, Espagne
Contrats de recherche, prix et distinctions
Prix et distinctions
2022
Jury’s Special Award for Pedagogical Innovation, SKEMA Business School, France
2020
Excelent Oral Presentation, 4th International Conference on Information System and Data Mining, ICISDM2020, Etats-Unis d'Amérique
2019
Extraordinary Doctorate Award, University of Seville
Contrats de recherche
2022
Horizon 2020 - HPC-Europa3 Transnational Access Programme, CSC Finland , Finlande
Autres activités de recherche
Relecteur pour :
Decision Support Systems, Finance Research Letters, IEEE Access, Expert Systems with Applications, Technological Forecasting and Social Change, Sustainability
Autres activités académiques
Depuis 2023
Association Française du Marketing, France
2023
Scientific Committee
2022 - 2023
Technical Committee ICISDM2023, Etats-Unis d'Amérique
2022 - 2023
CARMA2023 5th International Conference on Advanced Research Methods and Analytics
Depuis 2022
Steering Committee CARMA, Polytechnic University of Valencia, Espagne

Articles académiques revus

OLMEDILLA FERNANDEZ, M., ROCÍO MARTÍNEZ-TORRES, M. et TORAL, S. (2022). Prediction and modelling online reviews helpfulness using 1D Convolutional Neural Networks. Expert Systems with Applications, 198, pp. 116787.
OLMEDILLA FERNANDEZ, M., SEND, H. et TORAL, S.L. (2019). Identification of the unique attributes and topics within Smart Things Open Innovation Communities. Technological Forecasting and Social Change, 146, pp. 133-147.
OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, R. et TORAL, S. (2019). The super-hit effect and the long tail phenomenon in the context of electronic Word-of-Mouth. Decision Support Systems, 125, pp. 113120.
TESO, E., OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, M.R. et TORAL, S.L. (2018). Application of text mining techniques to the analysis of discourse in eWOM communications from a gender perspective. Technological Forecasting and Social Change, 129, pp. 131-142.
ARENAS-MARQUEZ, F.J., MARTINEZ-TORRES, M.R., OLMEDILLA FERNANDEZ, M. et TORAL, S.L. (2018). Identifying the Features of Reputable Users in eWOM Communities by Using Particle Swarm Optimization. Technological Forecasting and Social Change, 133, pp. 220-228.
OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, M.R. et TORAL, S.L. (2016). Harvesting Big Data in social science: A methodological approach for collecting online user-generated content. Computer Standards & Interfaces, pp. 79-87.
OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, M.R. et TORAL, S.L. (2016). Examining the power-law distribution among eWOM communities: A characterization approach of the long tail. Technology Analysis and Strategic Management, 28(5), pp. 601-613.
MARTINEZ-TORRES, R. et OLMEDILLA FERNANDEZ, M. (2016). Identification of innovation solvers in open innovation communities using swarm intelligence. Technological Forecasting and Social Change, 109, pp. 15-24.

Actes d’une conférence

OLMEDILLA FERNANDEZ, M., ROMERO MORENO, J.C. et BENAVENT, C. (2023). A BERT model approach on a large online reviews dataset: The role of context in evaluation.
OLMEDILLA FERNANDEZ, M., LI, Z., ESPINOSA-LEAL, L., LENDASSE, A. et BÖRK, K.M. (2022). Does streaming affects video game popularity?
OLMEDILLA FERNANDEZ, M., ROMERO, J.C., MARTÍNEZ TORRES, R. et TORAL, S. (2022). Applying NLP techniques to characterize what makes an online review trustworthy. Editorial Universitat Politècnica de València, pp. 189-195.
OLMEDILLA FERNANDEZ, M., ARENAS-MARQUEZ, F.J., MARTINEZ-TORRES, M.R. et TORAL, S. (2016). Identification of Influencers in eWord-of-Mouth communities using their Online Participation Features.
OLMEDILLA FERNANDEZ, M., ARENAS-MARQUEZ, F.J., MARTINEZ-TORRES, M.R. et TORAL, S. (2016). Features of Reputed Users in eWOM Using Evolutionary Computation.
OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, M.R. et TORAL, S. (2015). Examining Gender Discourse Differences in Shared Reviews about Books in eWOM.
MARTANEZ-TORRES, M.R., TORAL, S. et OLMEDILLA FERNANDEZ, M. (2015). A quantitative study of the evolution of Open Source Software Communities.
OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, M.R. et TORAL, S. (2015). A long tail study of eWOM communities.

Présentations dans des conférences

OLMEDILLA FERNANDEZ, M., ROMERO MORENO, J.C., MARTÍNEZ TORRES, R. et TORAL, S. (2023). Applying Transformers-based NLP Models to Explore Credibility in Different Product Categories in Amazon’s online reviews. Dans: CARMA2023-The 5th International Conference on Advanced Research Methods and Analytics. Seville.
OLMEDILLA FERNANDEZ, M., LI, Z. et ESPINOSA-LEAL, L. (2023). Predicting the helpfulness score of videogames of the STEAM platform. Dans: CARMA2023-The 5th International Conference on Advanced Research Methods and Analytics. Seville.
OLMEDILLA FERNANDEZ, M., LI, Z., ESPINOSA-LEAL, L., LENDASSE, A. et BÖRK, K.M. (2022). Does streaming affects video game popularity? Dans: The 12th International Conference on Extreme Learning Machines, ELM2022. Helsinki.
OLMEDILLA FERNANDEZ, M. (2022). Fundamentals of Artificial Intelligence and Machine Learning: Practical Business Applications. Dans: Cycle of Research Seminars Master and PhD Programme in Strategic Management and International Business Faculty of Economics and Business Administration University of Seville. Seville.
OLMEDILLA FERNANDEZ, M., ROMERO, J.C., MARTÍNEZ-TORRES, R. et TORAL, S. (2022). Applying NLP techniques to characterize what makes an online review trustworthy. Dans: 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Valencia.
OLMEDILLA FERNANDEZ, M., HAIKEL-ELSABEH, M. et ROMERO, J.C. (2022). A hybrid recommender system combining online review helpfulness and review positive sentiment to increase prediction accuracy. Dans: 6th International Conference on Information System and Data Mining, ICISDM2022. Silicon Valley.
OLMEDILLA FERNANDEZ, M. (2022). Understanding Artificial Intelligence: An overview of the basics and its applications. Dans: Graduate School and Research Unit, Arcada University of Applied Sciences, Helsinki.
OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, M.R. et TORAL, S. (2020). Identification of online reviews helpfulness using Neural Networks. Dans: CARMA2020, 3rd International Conference on Advanced Research Methods and Analytics. Valencia.
OLMEDILLA FERNANDEZ, M., HAIKEL-ELSABEH, M. et DE SMEDT, J. (2020). Recommending products based on users' positive word-of-mouth by combining a word-embedding model, Kernel Principal Component Analysis and SVD++ Collaborative Filtering. Dans: ICISDM2020 - 4th International Conference on Information System and Data Mining. Hilo.
TORAL, S., MARTINEZ-TORRES, M.R. et OLMEDILLA FERNANDEZ, M. (2019). Analysis of Online Reviews from the perspective of Search and Experience goods. Dans: International Conference on Social Informatics. Saint Petersburg.
OLMEDILLA FERNANDEZ, M. (2019). Recommending products based on users' activities and interests within an eWOM community by combining Principal Component Analysis and ALS Collaborative Filtering. Dans: ICISDM - International Conference on Information System and Data Mining. Houston.
OLMEDILLA FERNANDEZ, M. (2018). Improving postgraduate students' learning with the use of gamification Apps: The case of Kahoot! Dans: I International Workshop.Educational Innovation and Research. Sevilla.
OLMEDILLA FERNANDEZ, M., MARTINEZ-TORRES, M.R. et TORAL, S. (2018). Identification of helpful and not helpful online reviews within an eWOM community using text-mining techniques. Dans: International Conference on Advanced Research Methods and Analytics. Valencia.