Skip to main content

Research Repository

Advanced Search

Outputs (128)

Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation (2019)
Presentation / Conference Contribution
Tsakalidis, A., Liakata, M., Damoulas, T., & Cristea, A. I. (2018, September). Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation. Presented at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2018 Applied Data Science Track), Dublin

Predicting mental health from smartphone and social media data on a longitudinal basis has recently attracted great interest, with very promising results being reported across many studies. Such approaches have the potential to revolutionise mental h... Read More about Can We Assess Mental Health through Social Media and Smart Devices? Addressing Bias in Methodology and Evaluation.

Research on Prediction of Infectious Diseases, their spread via Social Media and their link to Education (2019)
Presentation / Conference Contribution
Aduragba, O. T., & Cristea, A. I. (2019, December). Research on Prediction of Infectious Diseases, their spread via Social Media and their link to Education. Presented at 4th International Conference on Information and Education Innovations - ICIEI 2019, Durham

Infectious diseases are a great plague, especially in low and middle income countries. Beyond the actual treatment, an important role is played by early prevention mechanisms, and education of society at large, about existing risks. This paper tackle... Read More about Research on Prediction of Infectious Diseases, their spread via Social Media and their link to Education.

Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses (2018)
Presentation / Conference Contribution
Cristea, A., Alamri, A., Kayama, M., Stewart, C., Alsheri, M., & Shi, L. (2018, October). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund, Sweden

Whilst a high dropout rate is a well-known problem in MOOCs, few studies take a data-driven approach to understand the reasons of such a phenomenon, and to thus be in the position to recommend and design possible adaptive solutions to alleviate it. I... Read More about Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses.

Demographic Indicators Influencing Learning Activities in MOOCs: Learning Analytics of FutureLearn Courses (2018)
Presentation / Conference Contribution
Shi, L., & Cristea, A. (2018, October). Demographic Indicators Influencing Learning Activities in MOOCs: Learning Analytics of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund

Big data and analytics for educational information systems, despite having gained researchers’ attention, are still in their infancy and will take years to mature. Massive open online courses (MOOCs), which record learner-computer interactions, bring... Read More about Demographic Indicators Influencing Learning Activities in MOOCs: Learning Analytics of FutureLearn Courses.

How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers (2018)
Presentation / Conference Contribution
Cristea, A., Alshehri, M., Alamri, A., Kayama, M., Stewart, C., & Shi, L. (2018, October). How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund

Data-intensive analysis of massive open online courses (MOOCs) is popular. Researchers have been proposing various parameters conducive to analysis and prediction of student behaviour and outcomes in MOOCs, as well as different methods to analyse and... Read More about How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers.

In-depth Exploration of Engagement Patterns in MOOCs (2018)
Presentation / Conference Contribution
Lei, S., & Cristea, A. (2018, December). In-depth Exploration of Engagement Patterns in MOOCs. Presented at Web Information Systems Engineering (WISE 2018), Dubai

With the advent of ‘big data’, various new methods have been proposed, to explore data in several domains. In the domain of learning (and e-learning, in particular), the outcomes lag somewhat behind. This is not unexpected, as e-learning has the addi... Read More about In-depth Exploration of Engagement Patterns in MOOCs.

Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum (2018)
Presentation / Conference Contribution
Tsakalidis, A., Aletras, N., Cristea, A., & Liakata, M. (2018, December). Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum. Presented at 2018 ACM Conference on Information and Knowledge Management (CIKM’18), Torino

Modelling user voting intention in social media is an important research area, with applications in analysing electorate behaviour, online political campaigning and advertising. Previous approaches mainly focus on predicting national general election... Read More about Nowcasting the Stance of Social Media Users in a Sudden Vote: The Case of the Greek Referendum.

Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses (2018)
Presentation / Conference Contribution
Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018, August). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund, Sweden

Whilst a high dropout rate is a well-known problem in MOOCs, few studies take a data-driven approach to understand the reasons of such a phenomenon, and to thus be in the position to recommend and design possible adaptive solutions to alleviate it. I... Read More about Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses.

How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers (2018)
Presentation / Conference Contribution
Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018, December). How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers. Presented at 27th International Conference on Information Systems Development (ISD2018), Lund, Sweden

Data-intensive analysis of massive open online courses (MOOCs) is popular. Researchers have been proposing various parameters conducive to analysis and prediction of student behaviour and outcomes in MOOCs, as well as different methods to analyse and... Read More about How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers.