Popularity Prediction for Social Media over Arbitrary Time Horizons
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
ACM Conference on Human Factors in Computing Systems (CHI)
“Time spent on platform” is a widely used measure in many studies examining social media use and well-being, yet the current literature presents unresolved findings about the relationship between time on platform and well-being. In this paper, we consider the moderating effect of people’s mindsets about social media — whether they think a platform is good or bad for themselves and for society more generally. Combining survey responses from 29,284 participants in 15 countries with server-logged data of Facebook use, we found that when people thought that Facebook was good for them and for society, time spent on the platform was not significantly associated with well-being. Conversely, when they thought Facebook was bad, greater time spent was associated with lower well-being. On average, there was a small, negative correlation between time spent and well-being and the causal direction is not known. Beliefs had a stronger moderating relationship when time-spent measures were self-reported rather than coming from server logs. We discuss potential mechanisms for these results and implications for future research on well-being and social media use.
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
Liqi Yan, Qifan Wang, Yiming Cu, Fuli Feng, Xiaojun Quan, Xiangyu Zhang, Dongfang Liu
Barlas Oğuz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih