Paper Info
Title
Detecting Implicit Expressions of Affect from Text using Semantic Knowledge on Common Concept Properties.
Abstract
Emotions are an important part of the human experience. They are responsible for the adaptation and integration in the environment, offering, most of the time together with the cognitive system, the appropriate responses to stimuli in the environment. As such, they are an important component in decision-making processes. In today's society, the avalanche of stimuli present in the environment (physical or virtual) makes people more prone to respond to stronger affective stimuli (i.e., those that are related to their basic needs and motivations-survival, food, shelter, etc.). In media reporting, this is translated in the use of arguments (factual data) that are known to trigger specific (strong, affective) behavioural reactions from the readers. This paper describes initial efforts to detect such arguments from text, based on the properties of concepts. The final system able to retrieve and label this type of data from the news in traditional and social platforms is intended to be integrated Europe Media Monitor family of applications to detect texts that trigger certain (especially negative) reactions from the public, with consequences on citizen safety and security.
Year
Venue
Keywords
2016
LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
emotion detection,media monitoring,argument mining,emotion triggers,common-sense knowledge,decision support
Field
DocType
Citations 
Semantic memory,Expression (mathematics),Information retrieval,Computer science,Natural language processing,Artificial intelligence
Conference
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Alexandra Balahur159340.19
Hristo Tanev245651.18