Gunrock: A Social Bot for Complex and Engaging Long Conversations
Dian Yu | Michelle Cohn | Yi Mang Yang | Chun Yen Chen | Weiming Wen | Jiaping Zhang | Mingyang Zhou | Kevin Jesse | Austin Chau | Antara Bhowmick | Shreenath Iyer | Giritheja Sreenivasulu | Sam Davidson | Ashwin Bhandare | Zhou Yu
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
Gunrock is the winner of the 2018 Amazon Alexa Prize, as evaluated by coherence and engagement from both real users and Amazon-selected expert conversationalists. We focus on understanding complex sentences and having in-depth conversations in open domains. In this paper, we introduce some innovative system designs and related validation analysis. Overall, we found that users produce longer sentences to Gunrock, which are directly related to users’ engagement (e.g., ratings, number of turns). Additionally, users’ backstory queries about Gunrock are positively correlated to user satisfaction. Finally, we found dialog flows that interleave facts and personal opinions and stories lead to better user satisfaction.
Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content
Weiming Wen | Songwen Su | Zhou Yu
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
With the increasing popularity of smart devices, rumors with multimedia content become more and more common on social networks. The multimedia information usually makes rumors look more convincing. Therefore, finding an automatic approach to verify rumors with multimedia content is a pressing task. Previous rumor verification research only utilizes multimedia as input features. We propose not to use the multimedia content but to find external information in other news platforms pivoting on it. We introduce a new features set, cross-lingual cross-platform features that leverage the semantic similarity between the rumors and the external information. When implemented, machine learning methods utilizing such features achieved the state-of-the-art rumor verification results.
- Zhou Yu 2
- Dian Yu 1
- Michelle Cohn 1
- Yi Mang Yang 1
- Chun-Yen Chen 1
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