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題名 Hidden advertorial detection on social media in Chinese
作者 張瑜芸
Chang, Yu-Yun
Ho, Meng-Ching;Chuang, Ching-Yun;Hsu, Yi-Chun
貢獻者 語言所
日期 2021-10
上傳時間 17-二月-2023 15:08:24 (UTC+8)
摘要 Nowadays, there are a lot of advertisements hiding as normal posts or experience sharing in social media. There is little research of advertorial detection on Mandarin Chinese texts. This paper thus aimed to focus on hidden advertorial detection of online posts in Taiwan Mandarin Chinese. We inspected seven contextual features based on linguistic theories in discourse level. These features can be further grouped into three schemas under the general advertorial writing structure. We further implemented these features to train a multi-task BERT model to detect advertorials. The results suggested that specific linguistic features would help extract advertorials.
關聯 Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021), Association for Computational Linguistics and Chinese Language Processing (ACLCLP), pp.243-251
資料類型 conference
dc.contributor 語言所
dc.creator (作者) 張瑜芸
dc.creator (作者) Chang, Yu-Yun
dc.creator (作者) Ho, Meng-Ching;Chuang, Ching-Yun;Hsu, Yi-Chun
dc.date (日期) 2021-10
dc.date.accessioned 17-二月-2023 15:08:24 (UTC+8)-
dc.date.available 17-二月-2023 15:08:24 (UTC+8)-
dc.date.issued (上傳時間) 17-二月-2023 15:08:24 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/143479-
dc.description.abstract (摘要) Nowadays, there are a lot of advertisements hiding as normal posts or experience sharing in social media. There is little research of advertorial detection on Mandarin Chinese texts. This paper thus aimed to focus on hidden advertorial detection of online posts in Taiwan Mandarin Chinese. We inspected seven contextual features based on linguistic theories in discourse level. These features can be further grouped into three schemas under the general advertorial writing structure. We further implemented these features to train a multi-task BERT model to detect advertorials. The results suggested that specific linguistic features would help extract advertorials.
dc.format.extent 107 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021), Association for Computational Linguistics and Chinese Language Processing (ACLCLP), pp.243-251
dc.title (題名) Hidden advertorial detection on social media in Chinese
dc.type (資料類型) conference