Language and the Internet

(Axel Boer) #1

The language of virtual worlds 187

of words per minute dropped.^20 The players would use more utter-
ances per minute, but put fewer words into them. Doubtless this is
due, as Cherny suggests, to the fact that people have to read other
players’ messages while they are typing their own, and the more
they have to read, think about, and react to, the less time they have
themselves to write. Moreover, when a lot of players are sending
short messages simultaneously, the screen is scrollingvery rapidly.
In passing, it seems to me that those players who are trying to study
or carry on some kind of job while joining in a MUD must have a
tough time – though I am impressed by Cherny’s report of a com-
ment, in relation to interactions on TinyMUD, that ‘it is possible
to do calculus homework and have tinyse xat the same time, if you
type quickly.’^21
MUDs also vary greatly with respect to the economy of expres-
sion associated with Netspeak interaction. Some groups evolve a
succinct pattern of interaction, their utterances taking up only the
left-hand side of the screen, with relatively few whole-screen lines: a
100-utterance sample from the ‘Gloria’ log,^22 excluding the ‘X says’
formula, produced an average of only 4.75 words per line, with
two-thirds of the messages less than 5 words – comparable to the
short lengths found in synchronous chatgroups (p. 156). On the
other hand, two other samples from the same site showed a much
fuller, more discursive set of direct-speech utterances: ‘Black Rose’
with an average of 8.7 words per utterance, and ‘Classic Fiasco’
with an average of 7.68 words, both of them displaying several sen-
tence sequences over 20 words in length.^23 Indirect speech (emotes)
were also an important feature of these two samples (not so with
‘Gloria’, where no emotes were used), and these showed a similar

(^20) Cherny (1999: 165ff.). In her material, it was very unusual to find seven speakers within
21 a single minute of data.
22 Cherny (1999: 36).
23 Cherny (1999:
155) found that most messages in her ElseMOO data were 5–13 words in length. Al-
though my samples were much shorter, their range was not quite the same, with the
MUD referred to at fn. 22 having a bias towards shorter messages and the others a more
even spread.

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