WordNet: a lexical database for English
Communications of the ACM
Virtual reviewers for collaborative exploration of movie reviews
Proceedings of the 5th international conference on Intelligent user interfaces
Dynamic generation of adaptive Internet-based courses
Journal of Network and Computer Applications
Personally tailored teaching in WHURLE using conditional transclusion
Proceedings of the 12th ACM conference on Hypertext and Hypermedia
User Modeling and User-Adapted Interaction
A model of textual affect sensing using real-world knowledge
Proceedings of the 8th international conference on Intelligent user interfaces
ELM-ART: An Intelligent Tutoring System on World Wide Web
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
AHA! The adaptive hypermedia architecture
Proceedings of the fourteenth ACM conference on Hypertext and hypermedia
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Using natural language processing to improve eRulemaking: project highlight
dg.o '06 Proceedings of the 2006 international conference on Digital government research
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Sensitive webpage classification for content advertising
Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising
Towards Inferring Sequential-Global Dimension of Learning Styles from Mouse Movement Patterns
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Supporting the Development of Mobile Adaptive Learning Environments: A Case Study
IEEE Transactions on Learning Technologies
Empirically building and evaluating a probabilistic model of user affect
User Modeling and User-Adapted Interaction
On the evolution of user interaction in Facebook
Proceedings of the 2nd ACM workshop on Online social networks
The adaptive web
Affective user modeling for adaptive intelligent user interfaces
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Smokey: automatic recognition of hostile messages
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Lexicon-based methods for sentiment analysis
Computational Linguistics
Analyzing user modeling on twitter for personalized news recommendations
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
From humor recognition to irony detection: The figurative language of social media
Data & Knowledge Engineering
Techniques and applications for sentiment analysis
Communications of the ACM
AngryEmail? emotion-based e-mail tool adaptation
IWAAL'12 Proceedings of the 4th international conference on Ambient Assisted Living and Home Care
Predicting personality using novel mobile phone-based metrics
SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Predicting user personality by mining social interactions in Facebook
Journal of Computer and System Sciences
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This paper presents a new method for sentiment analysis in Facebook that, starting from messages written by users, supports: (i) to extract information about the users' sentiment polarity (positive, neutral or negative), as transmitted in the messages they write; and (ii) to model the users' usual sentiment polarity and to detect significant emotional changes. We have implemented this method in SentBuk, a Facebook application also presented in this paper. SentBuk retrieves messages written by users in Facebook and classifies them according to their polarity, showing the results to the users through an interactive interface. It also supports emotional change detection, friend's emotion finding, user classification according to their messages, and statistics, among others. The classification method implemented in SentBuk follows a hybrid approach: it combines lexical-based and machine-learning techniques. The results obtained through this approach show that it is feasible to perform sentiment analysis in Facebook with high accuracy (83.27%). In the context of e-learning, it is very useful to have information about the users' sentiments available. On one hand, this information can be used by adaptive e-learning systems to support personalized learning, by considering the user's emotional state when recommending him/her the most suitable activities to be tackled at each time. On the other hand, the students' sentiments towards a course can serve as feedback for teachers, especially in the case of online learning, where face-to-face contact is less frequent. The usefulness of this work in the context of e-learning, both for teachers and for adaptive systems, is described too.