1. A computer implemented method comprising: accessing a digital document, wherein the digital document relates to one or more topics; generating a list of expert students, wherein the expert students have authored one or more annotations relating to a topic similar to the one or more topics in the digital document by: extracting similar documents from a database of digital documents; filtering the similar documents into a set of documents that one or more users have annotated; computing a confidence score for each annotation imported by a user; and computing a local user rank of each expert student based on the confidence score; ordering the list of expert students according to the local user rank, wherein the local user rank identifies a level of expertise of the expert students; and presenting the ordered list of expert students, where the ordered list comprises a pre-defined number of expert students with a level of expertise meeting a predefined threshold.
1. A computer implemented method comprising: accessing a digital document, wherein the digital document relates to one or more topics; generating a list of expert students, wherein the expert students have authored one or more annotations relating to a topic similar to the one or more topics in the digital document by: extracting similar documents from a database of digital documents; filtering the similar documents into a set of documents that one or more users have annotated; computing a confidence score for each annotation imported by a user; and computing a local user rank of each expert student based on the confidence score; ordering the list of expert students according to the local user rank, wherein the local user rank identifies a level of expertise of the expert students; and presenting the ordered list of expert students, where the ordered list comprises a pre-defined number of expert students with a level of expertise meeting a predefined threshold. 4. The method of claim 1 , further comprising: wherein computing the confidence score for each annotation comprises computing a confidence score for each annotation imported by the user accessing the digital document, wherein the confidence score is based on a test score of one or more users who imported the annotation, the test score an indication of a quality of the annotation.