  Stretched words like `heellllp' or `heyyyyy' are a regular feature of spoken
language, often used to emphasize or exaggerate the underlying meaning of the
root word. While stretched words are rarely found in formal written language
and dictionaries, they are prevalent within social media. In this paper, we
examine the frequency distributions of `stretchable words' found in roughly 100
billion tweets authored over an 8 year period. We introduce two central
parameters, `balance' and `stretch', that capture their main characteristics,
and explore their dynamics by creating visual tools we call `balance plots' and
`spelling trees'. We discuss how the tools and methods we develop here could be
used to study the statistical patterns of mistypings and misspellings, along
with the potential applications in augmenting dictionaries, improving language
processing, and in any area where sequence construction matters, such as
genetics.
