Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Microblog has been a popular media platform for reporting and propagating news. Hover, fake news spreading on microblogs would severely jeopardize its public credibility. To identify the truthfulness of news on microblogs, images are very crucial content. ,  explore the key role of image content in the task of automatic news verification on microblogs. Existing approaches to news verification depend on features extracted mainly from the text content of news tets, while image features for news verification are often ignored. According to our study, hover, images are very popular and have a great influence on microblogs news propagation. In addition, fake and real news events have different image distribution patterns. Therefore,  propose several visual and statistical features to characterize these patterns visually and statistically for detecting fake news. Experiments on a real-world multimedia dataset collected from Sina ibo validate the effectiveness of our proposed image features. The news verification performance of our method outperforms baseline methods. To the best of our knowledge, this is the first attempt that systematically explores image features on news verification task.
['Zhiwei Jin', 'Juan Cao', 'Yongdong Zhang', 'Jianshe Zhou', 'Qi Tian']
I am writing a research paper on a idea Novel Visual and Statistical Image Features for Microblogs News Verification
[{"from": "human", "value": "I am writing a research paper on a idea Novel Visual and Statistical Image Features for Microblogs News Verification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Microblog has been a popular media platform for reporting and propagating news. Hover, fake news spreading on microblogs would severely jeopardize its public credibility. To identify the truthfulness of news on microblogs, images are very crucial content. ,  explore the key role of image content in the task of automatic news verification on microblogs. Existing approaches to news verification depend on features extracted mainly from the text content of news tets, while image features for news verification are often ignored. According to our study, hover, images are very popular and have a great influence on microblogs news propagation. In addition, fake and real news events have different image distribution patterns. Therefore,  propose several visual and statistical features to characterize these patterns visually and statistically for detecting fake news. Experiments on a real-world multimedia dataset collected from Sina ibo validate the effectiveness of our proposed image features. The news verification performance of our method outperforms baseline methods. To the best of our knowledge, this is the first attempt that systematically explores image features on news verification task."}]