Papers with English Twitter
Identification of Multiword Expressions in Tweets for Hate Speech Detection (2022.lrec-1)
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| Challenge: | Multiword expression (MWE) identification in tweets is a complex task due to the complex linguistic nature of MWEs combined with the non-standard language use in social networks. |
| Approach: | They propose a new architecture for incorporating multiword expression features into tweets to improve their accuracy. |
| Outcome: | The proposed system outperforms existing systems on the hate speech detection task on English Twitter. |
Target-Based Offensive Language Identification (2023.acl-short)
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Marcos Zampieri, Skye Morgan, Kai North, Tharindu Ranasinghe, Austin Simmmons, Paridhi Khandelwal, Sara Rosenthal, Preslav Nakov
| Challenge: | Popular social media annotation taxonomies focus on the post level and token-level annotations are not available. |
| Approach: | They propose a new dataset for Target-based Offensive language identification that uses post-level and token-level annotations to identify offensive language on Twitter. |
| Outcome: | The proposed taxonomy can be used to annotate offensive language on English Twitter posts. |
Microblog Hashtag Generation via Encoding Conversation Contexts (N19-1)
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| Challenge: | Automated hashtag annotation plays an important role in content understanding for microblog posts. |
| Approach: | They propose to annotate hashtags with a novel sequence generation framework via viewing the hashtag as a short sequence of words. |
| Outcome: | The proposed model outperforms existing models on two large-scale datasets . it can generate rare and even unseen hashtags, which is not possible with existing models . |
Vocabulary Pyramid Network: Multi-Pass Encoding and Decoding with Multi-Level Vocabularies for Response Generation (P19-1)
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| Challenge: | Conventional methods employ a fixed vocabulary and one-pass decoding, which make them prone to safe and general responses and lack further refinement to the first generated raw sequence. |
| Approach: | They propose a Vocabulary Pyramid Network which integrates multi-pass encoding and decoding with multi-level vocabularies into response generation. |
| Outcome: | The proposed system outperforms strong baselines on English Twitter and Chinese Weibo datasets. |