Nowadays, internet languages, including emojis, memes, hashtags, and slang, have become vital in constructing online communities’ collective identities. However, all these forms of internet language can sometimes disempower people from other generations or cultures. This position paper presents an argument explaining how online forms of communication create social belonging for specific groups at the expense of users, and especially elderly people, due to interpretation hurdles. The present study aims to evaluate the relationship between the internet language and online collective identity, highlighting how patterns in internet language can inform human- computer interaction (HCI) by revealing how users’ express identity, inclusion, and exclusion online.

This study discusses the emojis employment that compensate for the absence of supralinguistic emotive cues in digital communication. Analyzing gender relations (Male-to-Male, Male-to-Female, Female-to-Male, Female-to-Female) as a social influence factor in emoji use, the research explores the use of anger-related emojis and their dual functions as emotion signals and intensifiers. Findings reveal women use more intense emojis toward men and less severe ones toward women, a pattern not observed in men when emphasizing emotions. Hence, the study contributes to the conceptual application of emotional expression via emojis within digital media, raising sentiments on gender variances and improving emotional intelligence in artificial intelligence systems to yield a more accurate human feeling interpretation.