No Country for Old Members User Lifecycl
No Country for Old Members: User Lifecycle and Linguistic Change in Online Communities Danescu-Niculescu-Mizil, C., West, R., Jurafsky, D., Leskovec, J., & Potts, C. (2013, May). No country for old members: User lifecycle and linguistic change in online communities. In Proceedings of the 22nd international conference on World Wide Web (pp. 307-318). ACM.
“users follow a determined lifecycle with respect to their susceptibility to linguistic change: early in her career, a user becomes increasingly receptive to the norms of the community up to about one third of her eventual lifespan, when she reaches a maximum synchrony with the language of the community (we will call this early period linguistic adolescence); from that point on, a gap between the user’s language and that of the community forms and increases until the moment she abandons the site. We show that this increasing gap is explained by the user ceasing to respond to changes in community norms: because the language of the community is constantly evolving a user that is unreceptive to this change will appear as fathering from the community.”
Possible task: member lifetime G. Dror, D. Pelleg, O. Rokhlenko, I. Szpektor. Churn prediction in new users of Yahoo! answers. Workshop on Community Question Answering on the Web at WWW, 2012.
There is extensive research covering the evolution of online communities [21, 28], the evolution of community members [2, 10, 16, 29, 32], and their participation patterns [1, 3, 26, 30, 31, 48] (see Section 6 for a discussion). But little is known about the interplay between user-level evolution and the evolution of the community at large, an issue which is the crux of this work.
Snapshot language models S. M. Katz. Estimation of probabilities from sparse data for the language model component of a speech recognizer. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1987.
—> What might be gained by training word vectors instead of using cross-entrpoy loss (basically just GloVe)
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