There is inherent information captured in the order in which we write words\nin a list. The orderings of binomials --- lists of two words separated by `and'\nor `or' --- has been studied for more than a century. These binomials are\ncommon across many areas of speech, in both formal and informal text. In the\nlast century, numerous explanations have been given to describe what order\npeople use for these binomials, from differences in semantics to differences in\nphonology. These rules describe primarily `frozen' binomials that exist in\nexactly one ordering and have lacked large-scale trials to determine efficacy.\n Online text provides a unique opportunity to study these lists in the context\nof informal text at a very large scale. In this work, we expand the view of\nbinomials to include a large-scale analysis of both frozen and non-frozen\nbinomials in a quantitative way. Using this data, we then demonstrate that most\npreviously proposed rules are ineffective at predicting binomial ordering. By\ntracking the order of these binomials across time and communities we are able\nto establish additional, unexplored dimensions central to these predictions.\n Expanding beyond the question of individual binomials, we also explore the\nglobal structure of binomials in various communities, establishing a new model\nfor these lists and analyzing this structure for non-frozen and frozen\nbinomials. Additionally, novel analysis of trinomials --- lists of length three\n--- suggests that none of the binomials analysis applies in these cases.\nFinally, we demonstrate how large data sets gleaned from the web can be used in\nconjunction with older theories to expand and improve on old questions.\n