Results 151 to 160 of about 387 (173)
Some of the next articles are maybe not open access.
Boost Clickbait Detection Based on User Behavior Analysis
2017Article in the web is usually titled with a misleading title to attract the users click for gaining click-through rate (CTR). A clickbait title may increase click-through rate, but decrease user experience. Thus, it is important to identify the articles with a misleading title and block them for specific users.
Hai-Tao Zheng 0002 +4 more
openaire +1 more source
A deep model based on Lure and Similarity for Adaptive Clickbait Detection
Knowledge-Based Systems, 2021Jiaming Zheng, Ke Yu, Xiaofei Wu
exaly
Clickbait detection on WeChat: A deep model integrating semantic and syntactic information
Knowledge-Based Systems, 2022Ke Yu, Hao Zhou, Xiaofei Wu
exaly
Attention-Fused Deep Relevancy Matching Network for Clickbait Detection
IEEE Transactions on Computational Social Systems, 2023Qing Meng, Bo Liu, Xiangguo Sun
exaly
Detection of Clickbait Content Spreaders on Online Social Networks
2022 5th International Conference on Information and Computer Technologies (ICICT), 2022Smita Ghosh +3 more
openaire +1 more source
Detecting Clickbait in Chinese Social Media by Prompt Learning
2023 26th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 2023Yin Wu +3 more
openaire +1 more source
Clickbait Headline Detection Using Supervised Learning Method
2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS), 2022Vincent +3 more
openaire +1 more source
Clickbait Detection Using Bi-LSTM Model
2023 International Conference on Computational Intelligence for Information, Security and Communication Applications (CIISCA), 2023Kapil Kumar Yadav, Nipun Bansal
openaire +1 more source