EVALUATION OF ATTITUDES OF MAKURDI RESIDENTS TO SOCIAL MEDIA REPRESENTATION OF THE 2016 FLOODS

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dc.contributor.authorTsokar, Aondoaver Karls David
dc.date.accessioned2023-12-14T08:46:53Z
dc.date.available2023-12-14T08:46:53Z
dc.date.issued2019-05-01
dc.description.abstractThe study, Evaluation of Attitudes of Markurdi Residents to Social media representation of the 2016 Floods in Benue State ’ interrogates how the people of Makurdi with access to social media platforms responded to reports disseminated through the various channels available to them during the period, how these reports affected/shaped their perception of the disaster and the reactions thereafter. Anchored on the Uses and Gratification as well as Diffusion of Innovation theories, the survey method of data collection was used to obtain both quantitative and qualitative statistics, from a sample population size of 400 where questionnaires were administered and personal interviews conducted with government officials. Findings show that Facebook was the most used channel to disseminate the information, other channels used include whats app, Myspace, Bebo, YouTube, 2go, Viber, Blackberry Messenger, Instagram, and Naijapals. The study concludes that social media provides the platform that enables participants within and outside Benue and the immediate environment to disseminate information and share their views on important issues while remaining anonymous. The study therefore recommends a legislation to regulate responsible use of the social media be enacted, users of social media platforms should realize that people believe the information they disseminate, they should therefore be sincere, objective and development focused in their reportage of eventsen_US
dc.identifier.urihttps://keffi.nsuk.edu.ng/handle/20.500.14448/6727
dc.language.isoenen_US
dc.publisherDEPARTMENT OF MASS COMMUNICATION, FACULTY OF SOCIAL SCIENCES, NASARAWA STATE UNIVERSITY, KEFFIen_US
dc.titleEVALUATION OF ATTITUDES OF MAKURDI RESIDENTS TO SOCIAL MEDIA REPRESENTATION OF THE 2016 FLOODSen_US
dc.typeThesisen_US

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