A model of textual affect sensing using real-world knowledge
Proceedings of the 8th international conference on Intelligent user interfaces
Visualizing the affective structure of a text document
CHI '03 Extended Abstracts on Human Factors in Computing 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
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Major topic detection and its application to opinion summarization
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Topic analysis using a finite mixture model
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
A knowledge-based approach to text classification
SIGHAN '02 Proceedings of the first SIGHAN workshop on Chinese language processing - Volume 18
Understanding how bloggers feel: recognizing affect in blog posts
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Deriving wishlists from blogs show us your blog, and we'll tell you what books to buy
Proceedings of the 15th international conference on World Wide Web
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Transient life: collecting and sharing personal information
OZCHI '06 Proceedings of the 18th Australia conference on Computer-Human Interaction: Design: Activities, Artefacts and Environments
Topic sentiment mixture: modeling facets and opinions in weblogs
Proceedings of the 16th international conference on World Wide Web
Whose thumb is it anyway?: classifying author personality from weblog text
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
The utility of linguistic rules in opinion mining
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
An emotionally intelligent user interface: modelling emotion for user engagement
OZCHI '07 Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces
Semi-supervised named entity recognition: learning to recognize 100 entity types with little supervision
Visualizing the affective structure of students interaction
ICHL'12 Proceedings of the 5th international conference on Hybrid Learning
Social reader: towards browsing the social web
Multimedia Tools and Applications
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Online journals (blogs) provide not only an outlet for emotional self-expression, but also a space for social interaction and commiseration through the exchange of personal stories. However, the massive extent of the blogosphere can overwhelm users, restricting their ability to make meaningful connections to fellow bloggers. In this article, we present a system, VIBES, that extracts the important topics from a blog, measures the emotions associated with those topics, and generates a suite of visualizations of this information. Unlike previous research, which has focused on extracting global trends in opinion across the blogosphere, VIBES focuses on depicting the emotional trajectories of the storylines that persist throughout the life experiences of the individual. In user tests, a majority of participants agreed that the visualizations revealed the author's current emotional state and emotional development over time. VIBES has potential applications both in connecting users via shared emotional profiles on social networks, as well as facilitating self-reflection through private user status displays. It also offers a fresh perspective for studying emotions and modeling how they change over time, which has a number of applications in affective computing, including the creation of emotionally responsive interfaces.