During the 1980s the proliferation of new technologies transformed the potential of the news media to provide a constant flow of global real-time news. Tiananmen Square and the collapse of communism symbolised by the fall of the Berlin Wall became major media events communicated to Western audiences instantaneously via TV news media. By the end of the decade the question was being asked as to what extent this ‘media pervasiveness’ had impacted upon government – particularly the process of foreign policy making. The new technologies appeared to reduce the scope for calm deliberation over policy, forcing policy-makers to respond to whatever issue journalists focused on. This perception was in turn reinforced by the end of the bipolar order and what many viewed as the collapse of the old anti-communist consensus which – it was argued – had led to the creation of an ideological bond uniting policy makers and journalists. Released from the ‘prism of the Cold
War’ journalists were, it was presumed, freer not just to cover the stories they wanted but to criticise US foreign policy as well. The phrase ‘CNN effect’ encapsulated the idea that real-time communications technology could provoke major responses from domestic audiences and political elites to global events.
Detecting Fake News using Machine Learning Algorithms