Title
A Method for Detecting Harmful Entries on Informal School Websites Using Morphosemantic Patterns.
Abstract
This paper presents a novel method of analyzing morphosemantic patterns in language to the detect cyberbullying, or frequently appearing harmful messages and entries that aim to humiliate other users. The morphosemantic patterns represent a novel concept, with the assumption that analyzed elements can be perceived as a combination of morphological information, such as parts of speech, and semantic information, such as semantic roles, categories, etc. The patterns are further automatically extracted from the data containing harmful entries (cyberbullying) and non-harmful entries found on the informal websites of Japanese high schools. These website data were prepared and standardized by the Human Rights Center in Mie Prefecture, Japan. The patterns extracted in this way are further applied to a document classification task using the provided data in 10-fold cross-validation. The results indicate that morphosemantic sentence representation can be considered useful in the task of detecting the deceptive and provocative language used in cyberbullying.
Year
DOI
Venue
2017
10.20965/jaciii.2017.p1189
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS
Keywords
Field
DocType
cyberbullying detection,morphosemantics,pattern extraction,semantic role labeling,natural language processing
World Wide Web,Computer science,Multimedia,Semantic role labeling
Journal
Volume
Issue
ISSN
21
7
1343-0130
Citations 
PageRank 
References 
0
0.34
4
Authors
6
Name
Order
Citations
PageRank
Michal Ptaszynski113225.47
Fumito Masui28727.22
Yoko Nakajima332.81
Yasutomo Kimura466.94
Rafal Rzepka518740.62
Kenji Araki634380.17