| Item type |
文献 / Documents(1) |
| 公開日 |
2019-11-14 |
| アクセス権 |
|
|
アクセス権 |
open access |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 出版タイプ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| タイトル |
|
|
タイトル |
Slang Analysis Based on Variant Information Extraction Focusing on the Time Series Topics |
|
言語 |
en |
| 著者 |
松本, 和幸
吉田, 稔
土屋, 誠司
北, 研二
任, 福継
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Recently, with the increase in the number of users of Social Networking Sites (SNS), online communications have become more and more common, raising the possibility of using big data on SNS to analyze the diversity of language. Japanese language uses a variety of character types that are combined to create words and phrases. Therefore, it is difficult to morphologically analyze such words and phrases, even though morphological analysis is a basic process in natural language processing. Words and phrases that are not registered in morphological analysis dictionaries are usually not defined strictly, and their semantic interpretation seems to vary depending on the individual. In this study, we chronologically analyze the topics related to slang on Twitter. In this paper, as a validation experiment, we conducted a topic analysis experiment chronologically by using the sequential Tweet data and discussing the difference of topic change according to the slang types. |
|
言語 |
en |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Slang |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Topic analysis |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Time-series analkysis |
| 書誌情報 |
en : International Journal of Advanced Intelligence
巻 8,
号 1,
p. 84-98,
発行日 2016-05
|
| 収録物ID |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
18833918 |
| 出版者 |
|
|
出版者 |
AIA International Advanced Information Institute |
|
言語 |
en |
| EID |
|
|
識別子 |
306381 |
|
識別子タイプ |
URI |
| 言語 |
|
|
言語 |
eng |
ijai_8_1_84.pdf (673 KB)
