We propose a Bayesian method of estimating a conditional distribution of data given metadata (e.g., the usage of a dialectal variant given a location) based on queries from a big data/social media source, such as Twitter. This distribution is structurally equivalent to those built from traditional experimental methods, despite lacking negative examples. Tests using Twitter to investigate the geographic distribution of dialectal forms show that this method can provide distributions that are tightly correlated with existing gold-standard studies at a fraction of the time, cost, and effort.
REF , proposes a method based on conditional probability to estimate the geographical distribution of linguistic features using Twitter.
Mapping Dialectal Variation by Querying Social Media
EACL
Computer Science