Papers with online conversation
Enhancing Online Grooming Detection via Backtranslation Augmentation (2025.coling-main)
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| Challenge: | Existing models to detect predatory conversations for online conversation platforms are lacking in real-world applications due to sparse distribution of predatory conversation data. |
| Approach: | They propose backtranslation augmentation to augment training datasets with more predatory conversations by using 3 neural translators to augment them. |
| Outcome: | The proposed model improves with fewer training epochs for better classification efficacy on 8 languages from 4 language families and shows that it is more efficient than previous models. |
RoomReader: A Multimodal Corpus of Online Multiparty Conversational Interactions (2022.lrec-1)
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Justine Reverdy, Sam O’Connor Russell, Louise Duquenne, Diego Garaialde, Benjamin R. Cowan, Naomi Harte
| Challenge: | The corpus of multimodal, multiparty conversational interactions explored in RoomReader can be used to study a wide range of phenomena in online multimodal interaction. |
| Approach: | They propose to use RoomReader to explore multimodal cues of conversational engagement and behavioural aspects of collaborative interaction in online environments. |
| Outcome: | The corpus was developed within the wider RoomReader Project to explore multimodal cues of conversational engagement and behavioural aspects of collaborative interaction in online environments. |
EuroGames16: Evaluating Change Detection in Online Conversation (L18-1)
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| Challenge: | a new method for detecting salient changes from on-line conversations is needed . linguistic preprocessing and time series are used to build a time series . |
| Approach: | They propose a framework for detecting salient changes from on-line conversations . they use linguistic preprocessing to build a time series and change point detection algorithms to detect salient change. |
| Outcome: | The proposed method can detect salient changes in on-line conversations with high accuracy. |
WikiConv: A Corpus of the Complete Conversational History of a Large Online Collaborative Community (D18-1)
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Yiqing Hua, Cristian Danescu-Niculescu-Mizil, Dario Taraborelli, Nithum Thain, Jeffery Sorensen, Lucas Dixon
| Challenge: | Compared to large-scale collections of conversations from social media, Wikipedia talk pages only capture a subset of all discussions and only accounts for the final form of each conversation. |
| Approach: | They propose to reconstruct a corpus that encompasses the complete history of conversations between Wikipedia contributors. |
| Outcome: | The proposed corpus extracts high quality data in both Chinese and English. |
ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining (2021.acl-long)
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| Challenge: | Abstractive text summarization has primarily focused on modeling news articles . lack of standardized datasets for summarizing online conversations is a major problem . |
| Approach: | They propose to crowdsource four new datasets for summarizing online conversations . they incorporate argument mining through graph construction to directly model issues, viewpoints, and assertions present in a conversation. |
| Outcome: | The proposed models are compared against widely-used conversation summarization datasets and show comparable or improved results. |
Continuity of Topic, Interaction, and Query: Learning to Quote in Online Conversations (2020.emnlp-main)
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| Challenge: | Quotations are crucial for successful explanations and persuasions in interpersonal communications. |
| Approach: | They propose to use an encoder-decoder neural framework to continue the context with a quotation via language generation to capture latent topics, interactions with the dialogue history, and coherence to the existing contents. |
| Outcome: | The proposed model outperforms state-of-the-art models on two large-scale datasets in English and Chinese and shows that topic, interaction, and query consistency are helpful to learn how to quote in online conversations. |