Visualising social media sentiment of perception towards autistic people

Mazlan, Umi Hanim and Ab Raji, Nurul Hidayah and Azma Fizal, Muhammad Hifzhan (2025) Visualising social media sentiment of perception towards autistic people. Journal of Media and Information Warfare (JMIW), 18 (2). pp. 151-158. ISSN 2821-3394
Abstract

This study aims to develop an interactive dashboard utilising big data visualisation to enhance public awareness of autistic individuals. The research involves analysing sentiment data from social media platforms to gain insights into public perceptions of autism. A visually engaging and informative dashboard was created using tools such as Power BI to effectively visualise these sentiments. The study begins with the extraction and analysis of sentiment data from social media platforms, focusing on comments related to autism. Python is employed for data cleaning to ensure accuracy and relevance. The roBERTa model, known for its robust performance in natural language processing, is utilised for sentiment classification. Data analysis is conducted using Hive on Cloudera to handle large datasets effectively. Subsequently, an interactive dashboard is developed using Power BI to visualise the sentiment analysis results. The dashboard is integrated into a website created with HTML and hosted for accessibility. Consequently, this study successfully analyses public sentiment towards autistic individuals. The developed interactive dashboard effectively visualises these sentiments by revealing the societal perceptions represented by the positive and negative keywords. The dashboard is expected to undergo user experience testing to assess its acceptance as a tool to enhance public perception and awareness towards autistic individuals.

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