This paper aims to analyse how age groups impact the use of social media language (SL) in online textual conversations, focusing on the type, polarity, and subjectivity of SL to explore identity representation across different age groups. During data collection in 2023, there were 4.76 billion social media users worldwide; hence, understanding the use of SL is essential for analysing how individuals express their emotions and identities online. SL consists of emoticons/emojis, abbreviations, and mixed language in textual conversations. For this study, a qualitative approach was used, with 46 participants from three age groups: 25-34, 35-44, and 45-54 engaging in mock group conversations for one hour using WhatsApp. The participants were separated into six group conversations. The findings show that the older age groups (35-44 and 45-54) prefer to discuss technical or professional topics, whereas the younger age groups (25-34) are more interested in games, food, entertainment, and fun. Furthermore, for the age group 25-34 there is a high usage of emoticons/emojis, whereas the age group 45-54 uses them the least. These findings indicate that age groups have a significant influence on the use of SL and topic preferences in textual conversations, providing insights that will be used to develop a Natural Language Processing (NLP) tool for online identity classification. This study enhances human-computer interaction by investigating how different age groups use SL in digital environments.
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