Studying the Impact Of D.P.SL Model on Online Identity Management

Abstract

This paper investigates online identities through social media language use, with a focus on classifying online identity within textual conversations. It sheds light on how Demographic (D) groups and Personality (P) impact the use of Social-Media Language (SL) for identity representation online. This study was conducted in 2023 when there were 4.76 billion social media users worldwide, making it essential to study how social media language is used in textual conversations to convey online identity. The study defines social media language as consisting of emoticons/emojis, abbreviations, and mixed language within textual conversations, which have become essential for expressing feelings and emotions during conversations. The D.P.SL based survey conducted for this work aimed to understand how demographic groups and personality are related to social media language. Based on the total number of social media user worldwide, 400 responses (required based on Cochran and Yamane’s formulae sample-size calculation) and the survey was distributed across various verified online survey exchange platforms. However, 406 responses were recorded with young people in age groups of 18-24 and 25-34 using social media language more as it has become a part of their social media habits. The study also found that emoticons/emojis and slang abbreviations with letter reduplication were quite common, making conversations lively and funny. Additionally, individuals whose primary language is not English use their native language but type in English for quick communication. Subsequent study is to be conducted using online mock group conversations between participating respondents to further understand correlations, causation, and concurrency on how ‘online identity’ is managed during online communications via social media language, its context of use, and polarity sentiment.