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All Journal Indonesian Journal of Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING Journal of Information Systems and Informatics
Chani, Tarirai
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Computer Science & IT

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Social Media and the COVID-19: South African and Zimbabwean Netizens’ Response to a Pandemic Mutanga, Murimo Bethel; Ureke, Oswelled; Chani, Tarirai
Indonesian Journal of Information Systems Vol 4, No 1 (2021): August 2021
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i1.4338

Abstract

Since the end of 2019, the world faced a major health crisis in the form of the Coronavirus (COVID-19) pandemic. To mitigate the impact of the pandemic, governments across the globe instituted measures such as restricting local and international travel and in many cases, ordering citizens to stay indoors. Considering the social and economic impact of these restrictions it becomes crucial to investigate internet citizens’ (netizens) perception about the precautionary measures adopted. The study is anchored in the digital public sphere theory, which treats social media applications as virtual platforms where netizens commune to share ideas and debate about issues that affect them. Social media platforms already have critical public views on the current pandemic. However, the majority of this data is unstructured and difficult to interpret. Natural language processing (NLP), on the other hand, makes the task of gathering and analysing vast amounts of textual data feasible. Extracting structured knowledge from natural language, however, comes with unique challenges due to diverse linguistic properties including abbreviation, spelling mistakes, punctuations, stop words and non-standard text. In this work, The Latent Dirichlet Allocation (LDA) algorithm was applied to tweeter data to extract topics discussed by netzens from Zimbabwe and South Africa.  The primary focus of this paper, is to comparatively explore the variety of topics that occupied twitter communities from the two countries. We examine whether or not the national identities that define and differentiate citizens of these countries also exist on Twitter as evident in the emerging topics. Furthermore, this work investigated public opinion by analysing how citizens discuss the issues around the COVID-19 pandemic on social media
The Problem of Data Extraction in Social Media: A Theoretical Framework Chani, Tarirai; Olugbara, Oludayo O; Mutanga, Bethel
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.585

Abstract

In today's rapidly evolving digital landscape, the pervasive growth of social media platforms has resulted in an era of unprecedented data generation. These platforms are responsible for generating vast volumes of data on a daily basis, forming intricate webs of patterns and connections that harbor invaluable insights crucial for informed decision-making. Recognizing the significance of exploring social media data, researchers have increasingly turned their attention towards leveraging this data to address a wide array of social research issues. Unlike conventional data collection methods such as questionnaires, interviews, or focus groups, social media data presents unique challenges and opportunities, demanding specialized techniques for its extraction and analysis. However, the absence of a standardized and systematic approach to collect and preprocess social media data remains a gap in the field. This gap not only compromises the quality and credibility of subsequent data analysis but also hinders the realization of the full potential inherent in social media data. This paper aims to bridge this gap by presenting a comprehensive framework designed for the systematic extraction and processing of social media data. The proposed framework offers a clear, step-by-step methodology for the extraction and processing of social media data for analysis. In an era where social media data serves as a pivotal resource for understanding human behavior, sentiment, and societal dynamics, this framework offers a foundational toolset for researchers and practitioners seeking to harness the wealth of insights concealed within the vast expanse of social media data.
Information Cascades in Professional Networks: A Graph-Based Study of LinkedIn Post Engagement Revesai, Zvinodashe; Mutanga, Murimo Bethel; Chani, Tarirai
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.10212

Abstract

Information cascades in professional networks represent a critical mechanism for knowledge transfer and career development, yet their dynamics remain poorly understood. This study presents a comprehensive empirical analysis of information cascades in LinkedIn professional networks, focusing on computer science professionals and academic-industry knowledge transfer. We analysed 50,000 CS professionals, 500,000 connections, and 100,000 technical posts over 12 months using a Modified Independent Cascade Model that incorporates professional context factors. Our analysis reveals that hybrid professionals, representing only 25% of the network, account for 52% of inter-cluster connections and achieve 2.8× higher cross-domain transfer rates. Educational content demonstrates superior cross-domain appeal (0.47) compared to research papers (0.23), with optimal posting windows between 10 AM-12 PM achieving 23% higher cross-domain engagement. Bridge users in academic-industry transitions show significantly higher transfer effectiveness (Cohen's d = 1.47, p < 0.001). These findings provide evidence-based strategies for optimising professional networking and knowledge dissemination across academic and industry domains
Co-Authors Mutanga, Bethel Mutanga, Murimo Bethel Olugbara, Oludayo O Revesai, Zvinodashe Ureke, Oswelled