Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-45111-9_41
Title: An introduction to concept-level sentiment analysis
Authors: Cambria, E. 
Keywords: AI
Big social data analysis
Concept-level sentiment analysis
NLP
Issue Date: 2013
Citation: Cambria, E. (2013). An introduction to concept-level sentiment analysis. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 8266 LNAI (PART 2) : 478-483. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-45111-9_41
Abstract: The ways people express their opinions and sentiments have radically changed in the past few years thanks to the advent of social networks, web communities, blogs, wikis, and other online collaborative media. The distillation of knowledge from the huge amount of unstructured information on the Web can be a key factor for marketers who want to create an image or identity in the minds of their customers for their product or brand. These online social data, however, remain hardly accessible to computers, as they are specifically meant for human consumption. The automatic analysis of online opinions, in fact, involves a deep understanding of natural language text by machines, from which we are still very far. To this end, concept-level sentiment analysis aims to go beyond a mere word-level analysis of text and provide novel approaches to opinion mining and sentiment analysis that enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. © Springer-Verlag 2013.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/116691
ISBN: 9783642451102
ISSN: 03029743
DOI: 10.1007/978-3-642-45111-9_41
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