International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Open Access | Fully Refereed | Peer Reviewed

ISSN: 2319-7064


Downloads: 193

Research Paper | Information Technology | Kenya | Volume 7 Issue 10, October 2018


Social Media Mining Methods Used to Improve Business Intelligence at Safaricom Public Limited Company

Caroline Kendi, Dr Collins Oduor


Abstract: The study sought to establish social media mining techniques that were used at Safaricom PLC. This study was anchored on the tenets of the General Systems Theory and the Technology Acceptance Model (TAM) and took on a descriptive survey design. The target population in the study comprised of 150 employees of Safaricom PLC in the social media and business development departments. It used simple random sampling, which saw 72employees of Safaricom PLC being sampled. A questionnaire was used as the main research instrument. The reliability of the study was tested using the Cronbach Alpha test and the validity test was ensured by consulting experts and supervisors of the study. The collected data was sorted, cleaned and coded into SPSS 23 for subsequent descriptive and inferential statistics. The analyzed data was presented using charts, figures and tables. The study found that text mining was used for social media mining at Safaricom PLC as well as clustering and visualization. The study concluded that social media mining methods improved business intelligence and significantly predicted business intelligence at Safaricom PLC. The study recommends that the organization can share the information mined to other departments which can be used to show where it is not performing well and therefore improve its performance.


Keywords: Business intelligence, social media mining, Safaricom Public Limited Company, social media mining techniques, social media


Edition: Volume 7 Issue 10, October 2018,


Pages: 185 - 192


How to Cite this Article?

Caroline Kendi, Dr Collins Oduor, "Social Media Mining Methods Used to Improve Business Intelligence at Safaricom Public Limited Company", International Journal of Science and Research (IJSR), https://www.ijsr.net/get_abstract.php?paper_id=ART20191746, Volume 7 Issue 10, October 2018, 185 - 192

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