FauxWard: a graph neural network approach to fauxtography detection using social media comments

Author:

Shang Lanyu,Zhang Yang,Zhang Daniel,Wang DongORCID

Funder

Directorate for Computer and Information Science and Engineering

Army Research Office

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Human-Computer Interaction,Media Technology,Communication,Information Systems

Reference60 articles.

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2. Chen J, Ma T, Xiao C (2018) Fastgcn: fast learning with graph convolutional networks via importance sampling. arXiv preprint arXiv:180110247

3. Cooper SD (2007) A concise history of the fauxtography blogstorm in the 2006 lebanon war. Am Commun J 9

4. Cooper BB (2013) Fast company. How twitter’s expanded images increase clicks, retweets and favorites. https://www.fastcompany.com/3022116/what-twitters-expanded-images-mean-for-clicks-retweets-and-favorites

5. Cui L, Wang S, Lee D (2019) Same: sentiment-aware multi-modal embedding for detecting fake news. In: Proceedings of the 2019 IEEE/ACM international conference on advances in social networks analysis and mining, pp 41–48

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