A Framework for Predicting Media Event Coverage
e-Journal of Social & Behavioural Research in Business
ISSN or ISBN
Purpose:Bias in the media, and especially with respect to the choice of stories to run, is often remarked upon but almost never quantified.The present discussion provides an overview of recent work in the literature on media bias,and then proposes a new method for objectively measuring the extent of this bias. In this way, the paper develops a framework for predicting media event coverage.
Design/methodology/approach: This paper introduces a new mathematical model based on theoretical considerations that include not only the number of people affected by a potentially newsworthy event, but also the possible political impact of the story being run.
Findings:The framework introduced is suitable for guiding future research on media bias and helps ameliorate the thorny issues surrounding attempts to avoid partisanship when assessing media bias in an unbiased fashion.The model also helps to predict which stories will receive media attention.
Originality:While the concept of media bias and misrepresentation is not new, there is surprisingly little that has been done to quantify or establish criteria for measuring the extent of this bias. In fact, theoretical progress in this area has been very slow in recent decades.This paper is a step towards remedying this situation.
Neymotin, Evsey and Neymotin, Florence, "A Framework for Predicting Media Event Coverage" (2018). HCBE Faculty Articles. 1100.