Paper Info
Title
Detecting Emotive Sentences with Pattern-based Language Modelling.
Abstract
This paper presents our research in detection of emotive (emotionally loaded) sentences. The task is defined as a text classification problem with an assumption that emotive sentences stand out both lexically and grammatically. The assumption is verified exper- imentally. The experiment is based on n-grams as well as more sophisticated patterns with disjointed elements. To deal with the sophisticated patterns a novel language modelling algorithm based on the idea of language combinatorics is applied. The results of experiments are explained with the standard means of Precision, Recall and balanced F-score. The algorithm also provides a refined list of most frequent sophisticated patterns typical for both emotive and non-emotive context.
Year
DOI
Venue
2014
10.1016/j.procs.2014.08.129
Procedia Computer Science
Keywords
Field
DocType
Brute Force Search Algorithms,Pattern Extraction,Language Modelling,Emotive expressions,Language Combinatorics ,
Computer science,Natural language processing,Artificial intelligence,Emotive,Recall,Language modelling,Machine learning
Conference
Volume
ISSN
Citations 
35
1877-0509
0
PageRank 
References 
Authors
0.34
5
4
Name
Order
Citations
PageRank
Michal Ptaszynski113225.47
Fumito Masui28727.22
Rafal Rzepka318740.62
Kenji Araki434380.17