The researcher saved all mobile-based instant message conversations for 1 week and for more of safety and for sure the copy of the conversation had sent to the email, the researcher had saved this data. Ordinary instant messaging conversations through the span of 1week were following the 1-week data gathering period.
From the gathered instant messaging conversations, the researcher chose all messages that were written by the member and disposed of all messages composed by others. The researcher selected a random start point in the document and counted out a 100-word sample for analyzing. Acronyms (e.g., lol) and word combination (e.g., wanna) were considered single ”words.” Punctuation and emojis were not tallied in the 100 words but rather were incorporated into the examinations. Since the aggregate number of analyzable data focuses per member was more noteworthy than 100 in many cases
Table 1 shows how we categorized new language utilize and provide cases for every category. We broadly sorted new language use into shortcuts, speaking to alterations of the spelling of particular words and phrases, and pragmatic device, portrayal changes that reflect practical parts of the aspects, And pragmatic devices into three smaller categories. We additionally scored obvious typographical errors and incorrect spellings.
Within the shortcuts category classification, we grouped slang words commonly found on the Web as insider word (e.g., a hottie is a very attractive and desirable person; fugly is something or someone that is extremely ugly). We classified words regularly shortened by removing at least one phoneme or tow morphemes as an abbreviation (e.g., as per Netlingo.com, prolly is an abbreviated type of probably) and compressions of various words into a single, phonetically spelled word (e.g., wanna for want to) as word combination. We classified regular acronyms (e.g., lol for laughing out loud or bf for boyfriend) an acronym. We characterized substitution of a word or part of a word with an alphabetic name (e.g., u for you) or a number (e.g., 2morrow for tomorrow) as alphabetic/number words. We characterized basic phonetic spellings (e.g., wat for what) as phonetic new language words. We arranged the utilization of lower situation where letters ought to be promoted (e.g., as in the first letter of a proper noun) as lower case. We didn’t check the first word on a line (see example in conversation window in Fig. 1) as a lower case blunder despite the fact that each line generally relates to a sentence; along these lines, overlooking case might be underrepresented in our checks. We classified exclusion of an apostrophe (e.g., thats for that’s) as a contraction. We did not score other punctuation omissions as we could not determine whether a line break in sending an instant message was being used to represent punctuation.