@InProceedings{doyle-EtAl:2017:Long,
  author    = {Doyle, Gabriel  and  Goldberg, Amir  and  Srivastava, Sameer  and  Frank, Michael},
  title     = {Alignment at Work: Using Language to Distinguish the Internalization and Self-Regulation Components of Cultural Fit in Organizations},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {603--612},
  abstract  = {Cultural fit is widely believed to affect the success of individuals and the
	groups to which they belong. Yet it remains an elusive, poorly measured
	construct. Recent research draws on computational linguistics to measure
	cultural fit but overlooks asymmetries in cultural adaptation. By contrast, we
	develop a directed, dynamic measure of cultural fit based on linguistic
	alignment, which estimates the influence of one person's word use on another's
	and distinguishes between two enculturation mechanisms: internalization and
	self-regulation. We use this measure to trace employees' enculturation
	trajectories over a large, multi-year corpus of corporate emails and find that
	patterns of alignment in the first six months of employment are predictive of
	individuals’ downstream outcomes, especially involuntary exit. Further
	predictive analyses suggest referential alignment plays an overlooked role in
	linguistic alignment.},
  url       = {http://aclweb.org/anthology/P17-1056}
}