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Knowledge-Based Approaches to Concept-Level Sentiment Analysis

Year: 2013

Type: article

Abstract: The guest editors introduce novel approaches to opinion mining and sentiment analysis that go beyond a mere word-level analysis of text and provide concept-level methods. Such approaches allow a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain.

Source: IEEE Intelligent Systems

DOI: 10.1109/mis.2013.45

Authors: Erik Cambria, Bjorn Schuller, Bing Liu, Haixun Wang, Catherine Havasi

Institutions: National University of Singapore, University of Illinois Chicago, Technical University of Munich, Microsoft Research Asia (China), Massachusetts Institute of Technology

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W2016279377

FWCI: 16.15

Cites:

Cited by: 134

Related to: 10