1. Lawrence Williams University of North Texas

2. Even if a real-time quantitative study of age as a variable using a large corpus may never be possible, the apparent-time method is a starting point for analyzing age as a sociolinguistic variable.

3.  Most online environments do not organize or label speakers by age or age group.  Even though it might be possible to know something about the age of people in online environments, such information is only available in private or protected areas of the Web.  Potential sources of data are overlooked since age cannot be determined (i.e., might not be considered as reliable or valid).

4.  van Compernolle (2008) Dating site (asynchronous)  Blattner & Williams (2011) Internet Relay Chat (synchronous)

8. "Consistent with the notions of age-grading (Labov, 1972, 1994) and the linguistic market (Sankoff & Laberge, 1978), it may be that once individuals enter the workforce their linguistic behaviors move in the direction of the standard written language, at least in some contexts. This conclusion is also in line with Coveney's (1996) findings with regard to variable ne in the informal spoken French of France" (p. 15). [Emphasis added]

10. ne presence % (n) ne absence % (n) Total % (n) 20 s 18% (114)82% (514)100% (628) 30 s 14% (72)86% (460)100% (532) 40 s 15% (66)85% (368)100% (434) 50 s 42% (184)58% (257)100% (441) Overall21% (436)79% (1,599)100% (2035)

11.  Although Age Group was selected as a statistically significant factor, its influence is not as great as that of Grammatical Subject.  The lack of a more complex coding scheme did not allow for (possibly) insightful partition analysis.

12.  van Compernolle (2011) Dating site (asynchronous)  Al-Rashdan (2010) Internet Relay Chat (synchronous)  Blattner & Williams (in progress) [replication of Al-Rashdan, 2010] Internet Relay Chat (synchronous)

14.  Age Group, Gender, and Diacritic were all selected as statistically significant factor groups.  Age Group and Gender (ranges 17 and 18, respectively) are not nearly as influential as Diacritic (range 54).  "In terms of Labov’s (1990) general principles of language change, this result suggests either stable variation (i.e., no change in progress) (Principle I; p. 210) or the emergence of accent/diacritic use as a ‘prestige variant’ (Principle Ia; p. 213)" (p. 139).

16. ne presence % (n) ne absence % (n) Total % (n) 20 s 47% (190)53% (213)100% (403) 50 s 56% (273)44% (216)100% (489) Overall 52% (463)48% (429)100% (892)

17.  Age Group was not selected as a statistically significant factor, yet it is clear that Grapheme influences variation a great deal.  A lack of a greater number of usable/valid factor groups prevents further in-depth analysis (e.g., partitioning).

20.  Although Age Group was selected as a statistically significant factor group, its influence is negligible compared to that of Grapheme.  Moreover, a partition analysis revealed that Age Group is significant in Session 2 (June), yet it is not in Session 1 (May).

21.  Although Age Group does indeed influence language variation, it does not usually seem to be the most influential factor with the exception of the results shown in the dating site study by van Compernolle (2008).  Different coding schemes and the selection of different independent variables make comparisons difficult, given the limited numbers of published work in this area.

22.  Only a handful of scholars are working on language variation/change in CMFD.  Focusing on additional factors will lead to a better understanding of discourse in general and computer-mediated discourse more specifically. It might be worthwhile, for example, to exploreTopic in greater detail (following Williams, 2009).

23.  van Compernolle, R. A. (2008). Language variation in online personal ads from Quebec. Language@Internet, 5, article 1.  Blattner, G., & Williams, L. (2011). L'emploi variable du ne dans le discours électronique synchrone : une étude variationniste en temps apparent [The variable use of ne in synchronous electronic discourse: An apparent-time variationist study]. Langage & Société, 138, 109-129.  van Compernolle, R. A. (2011). Use and variation of French diacritics on an Internet dating site. Journal of French Language Studies, 21(2), 131-148  Al-Rashdan, O. (2010). L’emploi variable des signes diacritiques dans le français tchaté : une étude variationniste en temps apparent [The variable use of diacritics in French chat: An apparent-time variationist study]. Unpublished masters thesis, University of North Texas. Available from http://digital.library.unt.edu/ark:/67531/metadc28382/m/?q=Al-Rashdan  Blattner, G., & Williams, L. (in progress). The influence of Age Group on the variable use of diacritics in synchronous computer-mediated French discourse.