Cmc Paper

Analyzing personal weblogs in Singapore side: the Wmatrix approach Vincent B.Y. Ooi, peckerwood K.W. burn mark & Andy K.L. Chiang National University of Singapore **Dictionary commentary of blog features with fast pace and conveniences ** mismatched items~~ flunk Both Figures 5 and 6 show the top 10 lexical items of the T and U corpora (O1) respectively, when compared with the spoken component of the BNC take station (O2). The statistical ranking is done in scathe of the log-likelihood (LL) value, which shows the overuse (with the plus sign; or underuse, with the minus sign) of the source principal sum (i.e. the blog corpus) against the reference corpus (i.e. the BNC verbalise Sampler). In Wmatrix, statistical significance begins with a LL value of almost 7, since 6.63 is the cut-off for 99% trustingness of significance (Rayson 2003, Rayson 2005). LL-scores 1. Computer-mediated items that are likely to be shared in the midst of the major varieties of English, including the following: a. Emoticons and treatment Markers: e.g. :) :X,*yummy*, ermmm, hahahaha, sheesh b. Abbreviations ( too in SMS/texting language): e.g. Tmr, pple, bf, lol, wtf (what the tell apart) c. germinal re-spellings (also in SMS/texting language), e.g. Dun (dont), noe (know), urself, nid (need), oso (also) d. late standard lexical impairment, e.g.

blog, chatroom e. Core lexical items, e.g. Hokkien, mahjong, bitch/fucker f. go on/Popular proper nouns, e.g. (Roger) Federer g. Informal E nglish, e.g. prolly (probably), hafta (have ! to) 2. Computer-mediated and varietal terms that may be said to characterize online Singapore English particularly, including the following: a. Abbreviations: e.g. sgh (Singapore General Hospital), cny (Chinese New Year) b. Discourse particles: e.g. de, lah, leh, liao, sia c. Neologisms: e.g. freshies (freshmen) d. Emoticons: e.g. =D (elation)...If you neediness to get a full essay, order it on our website: OrderCustomPaper.com

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