The Temperature of Feedback Chatbots: an Experiment in Humor Detection

Humor is one of the measures of human intelligence, and similarly, humor is a major indicator of chatbot intelligence. To make chatbot answers more lively and interesting, thus increasing the interaction and entertainment between users and bots and providing a more interesting user experience. This paper collects a large text dataset and use models such as humor detection and humor scoring to detect the humor ability of chatbots, and improve the future work based on the results obtained from the experiments. It is shown that the CNN model's ability to recognize the humorous elements in the text and score the humorous information in the chat content gradually improves with multiple detections. This experiment implements the detection of humor ability of chatbots. A rating mechanism can assist in enhancing the humor and interactivity of robots, improve the existing computer humor model, enhance computer understanding of natural language, and promote the further development of artificial intelligence.

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Publication Details

Journal
Transactions on Computer Science and Intelligent Systems Research
Published
2024-08-12
DOI
https://doi.org/10.62051/78a5k715
Primary Topic
Humor Studies and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

The Temperature of Feedback Chatbots: an Experiment in Humor Detection

Tianle Chen, Wu Qian, Yang Cao
Transactions on Computer Science and Intelligent Systems Research
Humor Studies and Applications
article

The Temperature of Feedback Chatbots: an Experiment in Humor Detection

Tianle Chen, Wu Qian, Yang Cao
article en

Abstract

Humor is one of the measures of human intelligence, and similarly, humor is a major indicator of chatbot intelligence. To make chatbot answers more lively and interesting, thus increasing the interaction and entertainment between users and bots and providing a more interesting user experience. This paper collects a large text dataset and use models such as humor detection and humor scoring to detect the humor ability of chatbots, and improve the future work based on the results obtained from the experiments. It is shown that the CNN model's ability to recognize the humorous elements in the text and score the humorous information in the chat content gradually improves with multiple detections. This experiment implements the detection of humor ability of chatbots. A rating mechanism can assist in enhancing the humor and interactivity of robots, improve the existing computer humor model, enhance computer understanding of natural language, and promote the further development of artificial intelligence.

Transactions on Computer Science and Intelligent Systems ResearchVol. 5
Hebei University of Technology (CN), Huazhong Agricultural University (CN), Zhejiang Gongshang University (CN)
Quality Education
Openalex Percentile: Top 83%
Humor Studies and Applications
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The Temperature of Feedback Chatbots: an Experiment in Humor Detection — Tianle Chen, Wu Qian, et al. · Transactions on Computer Science and Intelligent Systems Research (2024) | TGRS Research Map | TGRS