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 im...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-01-01
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| Series: | CAAI Transactions on Intelligence Technology |
| Subjects: | |
| Online Access: | https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1060 |
| _version_ | 1818644559833333760 |
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| author | Kazuyuki Matsumoto Fuji Ren Fuji Ren Masaya Matsuoka Minoru Yoshida Kenji Kita |
| author_facet | Kazuyuki Matsumoto Fuji Ren Fuji Ren Masaya Matsuoka Minoru Yoshida Kenji Kita |
| author_sort | Kazuyuki Matsumoto |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T00:16:47Z |
| format | Article |
| id | doaj.art-c25fed434f1d4428bfc7b8120a8655cc |
| institution | Directory Open Access Journal |
| issn | 2468-2322 |
| language | English |
| last_indexed | 2024-12-17T00:16:47Z |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | CAAI Transactions on Intelligence Technology |
| spelling | doaj.art-c25fed434f1d4428bfc7b8120a8655cc2022-12-21T22:10:40ZengWileyCAAI Transactions on Intelligence Technology2468-23222019-01-0110.1049/trit.2018.1060TRIT.2018.1060Slang feature extraction by analysing topic change on social mediaKazuyuki Matsumoto0Fuji Ren1Fuji Ren2Masaya Matsuoka3Minoru Yoshida4Kenji Kita5Graduate School of Technology, Industrial and Social Sciences, Tokushima UniversityGraduate School of Technology, Industrial and Social Sciences, Tokushima UniversityGraduate School of Technology, Industrial and Social Sciences, Tokushima UniversityGraduate School of Technology, Industrial and Social Sciences, Tokushima UniversityGraduate School of Technology, Industrial and Social Sciences, Tokushima UniversityGraduate School of Technology, Industrial and Social Sciences, Tokushima UniversityRecently, 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.https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1060Internetfeature extractionsocial networking (online)slang feature extractionanalysing topic changesocial mediayouth slangneologismInternet slangsocial networking sitesfresh informationautomatic information collectiondocument groupstarget slanggeneral wordsslang classification methodSNS |
| spellingShingle | Kazuyuki Matsumoto Fuji Ren Fuji Ren Masaya Matsuoka Minoru Yoshida Kenji Kita Slang feature extraction by analysing topic change on social media CAAI Transactions on Intelligence Technology Internet feature extraction social networking (online) slang feature extraction analysing topic change social media youth slang neologism Internet slang social networking sites fresh information automatic information collection document groups target slang general words slang classification method SNS |
| title | Slang feature extraction by analysing topic change on social media |
| title_full | Slang feature extraction by analysing topic change on social media |
| title_fullStr | Slang feature extraction by analysing topic change on social media |
| title_full_unstemmed | Slang feature extraction by analysing topic change on social media |
| title_short | Slang feature extraction by analysing topic change on social media |
| title_sort | slang feature extraction by analysing topic change on social media |
| topic | Internet feature extraction social networking (online) slang feature extraction analysing topic change social media youth slang neologism Internet slang social networking sites fresh information automatic information collection document groups target slang general words slang classification method SNS |
| url | https://digital-library.theiet.org/content/journals/10.1049/trit.2018.1060 |
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