<p>Abstract</p><p>This essay deals with the creation and usage of nicknames in synchronous CMC. Nicknames from four different IRC chat conversations related to three different topic groups have been examined. The method draws on Bechar-Israeli’s (1996) categorisation of nicknames, which has been adapted to suit the type of data sampled. Three research questions have been posed, which, in view of other studies related to this field of research (e.g. Ellison et al. 2006, Scheidt 2001, Chester & Gwynne 1998, etc.) have been examined to obtain information about the degree of anonymity and the topic-relatedness of nicknames used in chatrooms. The results show that users participating in synchronous CMC indeed follow topic-related rules for self-presentation and that anonymity has varying importance in different chatrooms.</p>

Abstract This essay deals with the creation and usage of nicknames in synchronous CMC. Nicknames from four different IRC chat conversations related to three different topic groups have been examined. The method draws on Bechar-Israeli’s (1996) categorisation of nicknames, which has been adapted to suit the type of data sampled. Three research questions have been posed, which, in view of other studies related to this field of research (e.g. Ellison et al. 2006, Scheidt 2001, Chester &amp; Gwynne 1998, etc.) have been examined to obtain information about the degree of anonymity and the topic-relatedness of nicknames used in chatrooms. The results show that users participating in synchronous CMC indeed follow topic-related rules for self-presentation and that anonymity has varying importance in different chatrooms.

After providing an historical overview of the French spelling system and orthographic variation, this study analyzes selected internal (i.e., linguistic) factors and one external (i.e., social) factor that can influence the use of diacritics in online French-language chat sessions. From a corpus of synchronous computer-mediated communication, 3,855 tokens of graphemes capable of bearing diacritics were coded with the following scheme: Letter, Diacritic, Grapheme (i.e., Letter and Diacritic combined), Date of Participation, and Age Group of Participant. A multivariate (VARBRUL) analysis determined that Grapheme exerts the most influence on variation.