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
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
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Emotions from text: machine learning for text-based emotion prediction
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Digital Intuition: Applying Common Sense Using Dimensionality Reduction
IEEE Intelligent Systems
Mining opinion features in customer reviews
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Discourse level opinion interpretation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Developing HEO human emotions ontology
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Common sense computing: from the society of mind to digital intuition and beyond
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
SenticSpace: visualizing opinions and sentiments in a multi-dimensional vector space
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part IV
Sentic computing: exploitation of common sense for the development of emotion-sensitive systems
COST'09 Proceedings of the Second international conference on Development of Multimodal Interfaces: active Listening and Synchrony
Sentic avatar: multimodal affective conversational agent with common sense
Proceedings of the Third COST 2102 international training school conference on Toward autonomous, adaptive, and context-aware multimodal interfaces: theoretical and practical issues
Sentic medoids: organizing affective common sense knowledge in a multi-dimensional vector space
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Switching between different ways to think: multiple approaches to affective common sense reasoning
COST'10 Proceedings of the 2010 international conference on Analysis of Verbal and Nonverbal Communication and Enactment
Visualizing sentiments in business-customer relations with metaphors
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Combining lexicon and learning based approaches for concept-level sentiment analysis
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
Towards a chinese common and common sense knowledge base for sentiment analysis
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
Classifying unlabeled short texts using a fuzzy declarative approach
Language Resources and Evaluation
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In a world in which millions of people express their opinions about commercial products in blogs, wikis, fora, chats and social networks, the distillation of knowledge from this huge amount of unstructured information can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product, brand or organization. Opinion mining for product positioning, in fact, is getting a more and more popular research field but the extraction of useful information from social media is not a simple task. In this work we merge AI and Semantic Web techniques to extract, encode and represent this unstructured information. In particular, we use Sentic Computing, a multi-disciplinary approach to opinion mining and sentiment analysis, to semantically and affectively analyze text and encode results in a semantic aware format according to different web ontologies. Eventually we represent this information as an interconnected knowledge base which is browsable through a multi-faceted classification website.