Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/5712
Title: A Framework for Social Media Data Mining and Analysis to Product and Service Development- Case of The Zimbabwean National Art Gallery
Authors: Kumbirayi Kwenda
Noreen Sarai
Tinashe Gwendolyn Zhou
Systems Analyst, Kunda.org, Harare, Zimbabwe
Computer Science, Midlands State University, Gweru, Zimbabwe
Information Systems, Midlands State University, Gweru, Zimbabwe
Keywords: Social Media
Data Mining
Sentiment Analysis
Knowledge Data Discovery
Issue Date: 14-Feb-2021
Publisher: TechnoScience Academy
Abstract: Social networks have become a vital component in personal life. People are addicted to social network features, updating their profile page and collaborating virtually with other members have become daily routines. Web data mining is a new trend in current research studies. This study sought to develop a framework for social media data mining and analysis for the betterment and advancement of products (art effects) and services (exhibitions) with in the contemporary art industry of Zimbabwe through a case study of the Zimbabwean National Art Gallery. The information for this paper was gathered through the use of in-depth interviews, questionnaires, key-word search and API from the organization’s social media twitter handle were used to get the data for analysis. Focus group participants were chosen from the National art gallery and a matching number was selected from the artist who makes the artworks which will be soles or exhibited through the national art gallery. The findings suggested that, yes it is possible to inform the next batch of products with information mined from analyzing the sentiments or reviews of the previous set of artworks. Hence with this in mind the researchers managed to develop a framework which can be used to implement social media mining in the art sector of Zimbabwe. The proposed framework tried to handle the major limitations in current web mining frameworks by handling challenges such as special symbols, slang use, Data Validity analysis, time frame, and methodologies.
URI: https://cris.library.msu.ac.zw//handle/11408/5712
Appears in Collections:Research Papers

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