Slang feature extraction by analysing topic change on social media

Recently, the authors often see words such as youth slang, neologism and Internet slang on social networking sites (SNSs) that are not registered on dictionaries. Since the documents posted to SNSs include a lot of fresh information, they are thought to be useful for collecting information. It is important to analyse these words (hereinafter referred to as ‘slang’) and capture their features for the improvement of the accuracy of automatic information collection. This study aims to analyse what features can be observed in slang by focusing on the topic. They construct topic models from document groups including target slang on Twitter by latent Dirichlet allocation. With the models, they chronologically the analyse change of topics during a certain period of time to find out the difference in the features between slang and general words. Then, they propose a slang classification method based on the change of features.

言語

書誌情報

en : CAAI Transactions on Intelligence Technology

巻 4, 号 1, p. 64-71, 発行日 2019-01-18

収録物ID

収録物識別子タイプ

ISSN

収録物識別子

24682322

出版者

The Institution of Engineering and Technology

言語

権利情報

言語

権利情報

This is an open access article published by the IET, Chinese Association for Artificial Intelligence and Chongqing University of Technology under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

EID

識別子

349155

識別子タイプ

URI

言語

eng

戻る

views

See details

	Views

Versions

Ver.1

2024-10-29 00:24:17.555481

Show All versions

Cite as

エクスポート

OAI-PMH

JPCOAR 2.0
JPCOAR 1.0
DublinCore
DDI

Other Formats

JSON
BIBTEX

インデックスリンク

インデックスツリー

アイテム