Twitter hate aspect extraction using association analysis and dictionary-based approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F17%3A50013660" target="_blank" >RIV/62690094:18450/17:50013660 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3233/978-1-61499-800-6-641" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-800-6-641</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/978-1-61499-800-6-641" target="_blank" >10.3233/978-1-61499-800-6-641</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Twitter hate aspect extraction using association analysis and dictionary-based approach

Popis výsledku v původním jazyce

Recent research regarding hate speech is in the domain of social sciences and psychology. From these trends, the dissemination of hate speech and antagonistic content in social media has not been extensively studies from the perspective of sentiment analysis. In this paper, the main studies concerned about aspect-based sentiment analysis through twitter as the most popular social media communication in the world as they have 313 million active users worldwide. This paper initiate to address the shortcomings of implied aspects specific for hate crime domain. The expected beneficial hate aspects can be extracted from twitter based on combination of both analysis. The evaluation with researcher&apos;s own Hate Crime Twitter Sentiment (HCTS) dataset and also Hate Speech Twitter Datasoft (HSTD) was shown that the proposed approach is effective and produces significantly better results than baselines method.

Název v anglickém jazyce

Twitter hate aspect extraction using association analysis and dictionary-based approach

Popis výsledku anglicky

Recent research regarding hate speech is in the domain of social sciences and psychology. From these trends, the dissemination of hate speech and antagonistic content in social media has not been extensively studies from the perspective of sentiment analysis. In this paper, the main studies concerned about aspect-based sentiment analysis through twitter as the most popular social media communication in the world as they have 313 million active users worldwide. This paper initiate to address the shortcomings of implied aspects specific for hate crime domain. The expected beneficial hate aspects can be extracted from twitter based on combination of both analysis. The evaluation with researcher&apos;s own Hate Crime Twitter Sentiment (HCTS) dataset and also Hate Speech Twitter Datasoft (HSTD) was shown that the proposed approach is effective and produces significantly better results than baselines method.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Frontiers in Artificial Intelligence and Applications

ISBN

978-1-61499-799-3

ISSN

0922-6389

e-ISSN

neuvedeno

Počet stran výsledku

11

Strana od-do

641-651

Název nakladatele

IOS press

Místo vydání

Amsterdam

Místo konání akce

Kitakyushu; Japan

Datum konání akce

26. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—