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Rumors influence: Toward a dynamic social impact theory of rumor . In Science of social influence: Advances and future progress , pages 271 -- 296 , 2007 . N. Difonzo and P. Bordia. Rumors influence: Toward a dynamic social impact theory of rumor. In Science of social influence: Advances and future progress, pages 271--296, 2007."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/557"},{"key":"e_1_3_2_1_8_1","first-page":"101","volume-title":"ICWSM","author":"Friggeri A.","year":"2014","unstructured":"A. Friggeri , L. Adamic , D. Eckles , and J. Cheng . Rumor cascades . In ICWSM , pages 101 -- 110 , 2014 . A. Friggeri, L. Adamic, D. Eckles, and J. Cheng. Rumor cascades. In ICWSM, pages 101--110, 2014."},{"key":"e_1_3_2_1_9_1","volume-title":"DRAW: A recurrent neural network for image generation. arXiv preprint arXiv:1502.04623","author":"Gregor K.","year":"2015","unstructured":"K. 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