Une nouvelle approche linguistique pour ...
Document type :
Partie d'ouvrage
Title :
Une nouvelle approche linguistique pour évaluer l'opinion des usagers dans les réseaux sociaux
Author(s) :
Lancieri, Luigi [Auteur]
Nouveaux Outils pour La Coopération et l'Education [NOCE]
Leprêtre, Eric [Auteur]
Nouveaux Outils pour La Coopération et l'Education [NOCE]
Nouveaux Outils pour La Coopération et l'Education [NOCE]
Leprêtre, Eric [Auteur]
Nouveaux Outils pour La Coopération et l'Education [NOCE]
Scientific editor(s) :
Przemysław Kazienko, Nitesh Chawla
Book title :
Application of Social Media and Social Network Analysis
Publisher :
Springer International Publishing
Publication date :
2015-05-29
ISBN :
978-3-319-19002-0
English keyword(s) :
Sentiment analysis
Human expression
Text-mining
Adaptive classification
Length of text
Human expression
Text-mining
Adaptive classification
Length of text
HAL domain(s) :
Informatique [cs]/Interface homme-machine [cs.HC]
Informatique [cs]/Traitement du texte et du document
Informatique [cs]/Réseaux sociaux et d'information [cs.SI]
Informatique [cs]/Traitement du texte et du document
Informatique [cs]/Réseaux sociaux et d'information [cs.SI]
English abstract : [en]
This article describes an automated technique that allows to differentiate texts expressing a positive or a negative opinion. The basic principle is based on the observation that positive texts are statistically shorter ...
Show more >This article describes an automated technique that allows to differentiate texts expressing a positive or a negative opinion. The basic principle is based on the observation that positive texts are statistically shorter than negative ones. From this observation of the psycholinguistic human behavior, we derive a heuristic that is employed to generate connoted lexicons with a low level of prior knowledge. The lexicon is then used to compute the level of opinion of an unknown text. Our primary motivation is to reduce the need of the human implication (domain and language) in the generation of the lexicon in order to have a process with the highest possible autonomy. The resulting adaptability would represent an advantage with free or approximate expression commonly found in social networks environment.Show less >
Show more >This article describes an automated technique that allows to differentiate texts expressing a positive or a negative opinion. The basic principle is based on the observation that positive texts are statistically shorter than negative ones. From this observation of the psycholinguistic human behavior, we derive a heuristic that is employed to generate connoted lexicons with a low level of prior knowledge. The lexicon is then used to compute the level of opinion of an unknown text. Our primary motivation is to reduce the need of the human implication (domain and language) in the generation of the lexicon in order to have a process with the highest possible autonomy. The resulting adaptability would represent an advantage with free or approximate expression commonly found in social networks environment.Show less >
Language :
Anglais
Audience :
Internationale
Popular science :
Non
Collections :
Source :