Outputs (127)

Real-time timeline summarisation for high-impact events in Twitter (2016)
Presentation / Conference Contribution
Zhou, Y., Kanhabua, N., & Cristea, A. (2016, August). Real-time timeline summarisation for high-impact events in Twitter. Presented at ECAI 2016, The Hague

Twitter has become a valuable source of event-related information, namely, breaking news and local event reports. Due to its capability of transmitting information in real-time, Twitter is further exploited for timeline summarisation of high-impact e... Read More about Real-time timeline summarisation for high-impact events in Twitter.

Motivational gamification strategies rooted in self-determination theory for social adaptive E-Learning (2016)
Presentation / Conference Contribution
Cristea, A., & Shi, L. (2016, December). Motivational gamification strategies rooted in self-determination theory for social adaptive E-Learning. Presented at Intelligent Tutoring Systems, 13th International Conference, ITS 2016, Zagreb

This study uses gamification as the carrier of understanding the motivational benefits of applying the Self-Determination Theory (SDT) in social adaptive e-learning, by proposing motivational gamification strategies rooted in SDT, as well as developi... Read More about Motivational gamification strategies rooted in self-determination theory for social adaptive E-Learning.

Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia (2016)
Presentation / Conference Contribution
Zhou, Y., Demidova, E., & Cristea, A. (2016, April). Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia. Presented at SAC 2016, 31st ACM Symposium on Applied Computing, Pisa

In this paper we take an important step towards better understanding the existence and extent of entity-centric language-specific bias in multilingual Wikipedia, and any deviation from its targeted neutral point of view. We propose a methodology usin... Read More about Who likes me more? Analysing entity-centric language-specific bias in multilingual Wikipedia.

Towards detection of influential sentences affecting reputation in Wikipedia (2016)
Presentation / Conference Contribution
Zhou, Y., & Cristea, A. (2016, December). Towards detection of influential sentences affecting reputation in Wikipedia. Presented at ACM Web Science Conference 2016, Hannover

Wikipedia has become the most frequently viewed online encyclopaedia website. Some sentences in Wikipedia articles have direct and obvious impact on people's opinions towards the mentioned named entities. This paper defines and tackles the problem of... Read More about Towards detection of influential sentences affecting reputation in Wikipedia.

How emotions stimulate people affected by cancer to use personalised health websites (2015)
Journal Article
Hadzidedic Bazdarevic, S., & Cristea, A. I. (2015). How emotions stimulate people affected by cancer to use personalised health websites. Knowledge management & e-learning: an international journal, 7(4), 658-676

This paper focuses on helping people affected by cancer – which is the leading cause of death worldwide - by identifying their personalisation needs for health websites. The aim is to identify a set of personalisation features that users prefer on th... Read More about How emotions stimulate people affected by cancer to use personalised health websites.

What do people affected by cancer talk about online? Text analysis of online cancer community usage in Bosnia and Herzegovina (2015)
Presentation / Conference Contribution
Hadzidedic Bazdarevic, S., & Cristea, A. I. (2015, November). What do people affected by cancer talk about online? Text analysis of online cancer community usage in Bosnia and Herzegovina. Presented at Fifth International Conference on Social Medial Technologies, Communication and Informatics (SOTICS), Barcelona, Spain

Studies report that health information searching is among the top three activities on the Internet. Internet resources are a good alternative for initial information and health managing support, due to their accessibility and availability. However, l... Read More about What do people affected by cancer talk about online? Text analysis of online cancer community usage in Bosnia and Herzegovina.

A Taxonomy-Based Evaluation of Personalized E-Advertisement (2015)
Presentation / Conference Contribution
Al Qudah, D. A., Cristea, A. I., Hadzidedic Bazdarevic, S., Al-Saqqa, S., & Al-Sayyad, R. M. (2015, October). A Taxonomy-Based Evaluation of Personalized E-Advertisement. Presented at IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, Liverpool, UK

The art of personalized e-advertising relies in attracting a user attention to the recommended product, as it relates to their taste, interest and data. Whilst in practice, companies attempt various forms of personalization, research of e-advertising... Read More about A Taxonomy-Based Evaluation of Personalized E-Advertisement.

Learners Thrive When Using Multifaceted Open Social Learner Models (2015)
Journal Article
Shi, L., & Cristea, A. I. (2015). Learners Thrive When Using Multifaceted Open Social Learner Models. IEEE MultiMedia, 23(1), 36-47. https://doi.org/10.1109/mmul.2015.93

This article explores open social learner modeling (OSLM)-a social extension of open learner modeling (OLM). A specific implementation of this approach is presented by which learners' self-direction and self-determination in a social e-learning conte... Read More about Learners Thrive When Using Multifaceted Open Social Learner Models.

WarwickDCS : from phrase-based to target-specific sentiment recognition (2015)
Presentation / Conference Contribution
Townsend, R., Tsakalidis, A., Zhou, Y., Wang, B., Liakata, M., Zubiaga, A., Cristea, A., & Procter, R. (2015, June). WarwickDCS : from phrase-based to target-specific sentiment recognition. Presented at 9th International Workshop on Semantic Evaluation (SemEval 2015), Denver

We present and evaluate several hybrid systems for sentiment identification for Twitter, both at the phrase and document (tweet) level. Our approach has been to use a novel combination of lexica, traditional NLP and deep learning features. We also an... Read More about WarwickDCS : from phrase-based to target-specific sentiment recognition.

Predicting elections for multiple countries using Twitter and polls (2015)
Journal Article
Tsakalidis, A., Papadopoulos, S., Cristea, A., & Kompatsiaris, Y. (2015). Predicting elections for multiple countries using Twitter and polls. IEEE Intelligent Systems, 30(2), 10-17. https://doi.org/10.1109/mis.2015.17

The authors' work focuses on predicting the 2014 European Union elections in three different countries using Twitter and polls. Past works in this domain relying strictly on Twitter data have been proven ineffective. Others, using polls as their grou... Read More about Predicting elections for multiple countries using Twitter and polls.