Being a social network, application of social media has spread with a high momentum because of social interconnectivity that links friends and relatives. The Diffusion of innovation theory explains the trend that the social media has adopted and offers a basis for forecasting its future orientation. According to the theory, invention gains popularity and commands the society’s attention until a time when such attention fades. Rogers, the theory’s developer, proposed four stages that are expected of the social media, and its effects on US elections, in the future. The first stage of the model involves adoption by a small section of the society, innovators, who are willing to venture the innovation immediately after its development. The population section embraces possible risks that may discourage others. Following the innovators’ initiative is the adoption of a technology by early adopters whose population is higher than that of innovators. The population segment identifies leaders who do not need persuasion into a technology’s application and are flexible to implementing innovations. A larger percentage of the population into an innovation is the early majority who relies on evidence of the technology’s effects before adoption and an approximately equivalent proportion, the late majority, follows them. New users of the innovation then reduce as the model gets into the laggards’ phase (Boston University 1; Baran and Davis 282). The model therefore offers an insight into the possible trend and effects of the social media in the United States and two perspectives apply. If the people who adopt the social media technology at its earlier stages continue with its application then a cumulative impact can be derived over time because the social media will have a continually expanding audience. This however identifies the role of determining the media’s ability to retain users. Established rate of users’ retention also offers a basis for understanding trend of application and knowledge of the current stage of the innovation, based on the Diffusion of Innovation theory. The model’s variability with time can then offer insight into the future effects of social media on the elections. The theory further suggests an innovation’s effect of diminishing old media forms as the society adopts a new media application (Boston University 1). Shaw’s curve of the old media also offers a basis for understanding the trend in effect of the social media on US elections. Like in the diffusion theory, Shaw explains that an innovation gains popularity until a maximum level of audience before the number starts to decline and the time for the cycle depends on the scope of a preceding innovation or a newly developed innovation. Development of a better innovation may for example facilitate the cycle as the society moves to operate the new development. These concepts therefore offers the basis for understanding possible trends of the effect of social media on the elections that can be forecasted with knowledge of previous innovations and speculations of development of new applications for mass communication. Existing data over internet use that indicates high percentages suggests that application of the social media for communication is in advanced stages of the diffusion theory model. Application beyond 60 percent of the adult population indicates possibility of a late majority stage
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