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Authors: Kristína Machová and Ján Birka

Affiliation: Department of Cybernetics and Artificial Intelligence, Technical University of Košice, Letná 9, Košice and Slovakia

Keyword(s): Sentiment Analysis, Web Trends, Antisocial Behaviour, Online Discussion, Lexicon Approach.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Information Extraction ; Interactive and Online Data Mining ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Soft Computing ; Symbolic Systems ; Web Mining

Abstract: The paper presents an approach to extraction of current web trends for research into automated recognition of antisocial behaviour in online discussions. Antisocial behaviour is a drawback of online discussions as compared to their advantages such as wisdom of crowds and collective intelligence. The first step to recognition of antisocial behaviour is the identification of web trends connected with it. These are studied in dynamic conditions using sentiment analysis as a webometric. A new sentiment analysis method based on a lexicon was developed. Two modifications of the lexicon sentiment analysis method were designed and tested involving NLP (natural language processing) and an original technique for negations and intensifications processing. The most effective sentiment classification method was used for the extraction of web trends. Extracted web trends were analysed in a dynamic way and findings of this analysis were compared to known historical events.

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Paper citation in several formats:
Machová, K. and Birka, J. (2019). Sentiment Analysis of Web Trends for the Antisocial Behaviour Detection. In Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KDIR; ISBN 978-989-758-382-7; ISSN 2184-3228, SciTePress, pages 450-457. DOI: 10.5220/0008349104500457

@conference{kdir19,
author={Kristína Machová. and Ján Birka.},
title={Sentiment Analysis of Web Trends for the Antisocial Behaviour Detection},
booktitle={Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KDIR},
year={2019},
pages={450-457},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008349104500457},
isbn={978-989-758-382-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2019) - KDIR
TI - Sentiment Analysis of Web Trends for the Antisocial Behaviour Detection
SN - 978-989-758-382-7
IS - 2184-3228
AU - Machová, K.
AU - Birka, J.
PY - 2019
SP - 450
EP - 457
DO - 10.5220/0008349104500457
PB - SciTePress

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