Popularity Prediction for Social Media over Arbitrary Time Horizons
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
Conference on Human Factors in Computing Systems (CHI)
Despite significant advances in automated spam detection, some spam content manages to evade detection and engage users. While the spam supply chain is well understood through previous research, there is little understanding of spam consumers. We focus on the demand side of the spam equation examining what drives users to click on spam via a largescale analysis of de-identified, aggregated Facebook log data (n=600,000). We find (1) that the volume of spam and clicking norms in a users’ network are significantly related to individual consumption behavior; (2) that more active users are less likely to click, suggesting that experience and internet skill (weakly correlated with activity level) may create more savvy consumers; and (3) we confirm previous findings about the gender effect in spam consumption, but find this effect largely corresponds to spam topics. Our findings provide practical insights to reduce demand for spam content, thereby affecting spam profitability.
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
Carole-Jean Wu, Ramya Raghavendra, Udit Gupta, Bilge Acun, Newsha Ardalani, Kiwan Maeng, Gloria Chang, Fiona Aga Behram, James Huang, Charles Bai, Michael Gschwind, Anurag Gupta, Myle Ott, Anastasia Melnikov, Salvatore Candido, David Brooks, Geeta Chauhan, Benjamin Lee, Hsien-Hsin S. Lee, Bugra Akyildiz, Max Balandat, Joe Spisak, Ravi Jain, Mike Rabbat, Kim Hazelwood
Liqi Yan, Qifan Wang, Yiming Cu, Fuli Feng, Xiaojun Quan, Xiangyu Zhang, Dongfang Liu