खंड 2 No. Issue-08,Oct, 2025 ,pg-1713-1734 (2025): Context-Aware Sentiment Detection Using Multilingual Emojis, Slang, and Cultural Expressions in Social Networks

Abstract

The rigorous growth of social networking platforms demand
connectivity with people around the globe and transformed digital
communication using multilingual applications, emoji, slang,
sarcasm, and culturally influenced expressions. Traditional ways
of sentiment analysis systems often struggle to capture modern
interpretation of the emotional side of digital communication. This
research investigates how context-aware sentiment detection can
improve emotion interpretation of people across digital platforms.
This research adopts an exploratory design and secondary data
collection method to examine the impact of contextual analysis in
sentiment analysis across digital platforms. This research also
referred to thematic analysis to build a more structural realm
which can capture the factors that influence sentiment
classification accuracy. This study concluded that multilingual
context analysis, emoji interpretation, slang updates, and
appropriate cultural knowledge can minimise this chance of wrong
interpretation. The findings revealed a deep learning about
contextual emotions, references, and cultural significance can
improve sentiment detection performance in digital
communication. Advanced integration of Natural Language
Processing techniques can reduce the level of emotional
misinterpretation and provide a more adaptive mechanism to
support reliable social media analytics across various digital
domains.
Keywords: Context-aware Sentiment Analysis, Multilingual
Communication, Emojis, Internet Slang, Sentiment Detection, Social Networks