Why is news biased

In a mediatized environment, where news values and selection biases have become more prominent, discrepancies might arise between what happens in the world and how media portray it. As negativity and distortion biases have grown with time Farnsworth and Lichter , media are likely to progressively overrepresent the frequency of negative and isolated events and create a biased reflection of reality.

Thus, media, over time, might follow their own logic more instead of being guided by actual trends in the world van der Meer et al. Extant research has observed such discrepancies between media attention and real-world developments. For example, research has shown how immigration news predominantly focuses on threats and negativity van Klingeren et al. Comparable findings can be found in research on crime news that has shown how news attention for crime has consistently increased and does not always reflect actual crime rates Paulsen ; Smolej and Kivivuori Also, the relative media attention for aviation accidents is found to rise rather than follow the downward trend of actual accidents van der Meer et al.

As the current study is interested in the role news media play in the construction of risk perceptions regarding aviation and road accidents, we expect to observe similar patterns in news attention for these incidents.

In other words, it is expected that over time news media pay more attention to these negative events—i. H1: The frequency with which news media report on negative incidents—i. H2: There is a discrepancy between the frequency of occurrence of negative incidents—i. Next, when comparing aviation and road accidents, it can be expected that in mediatized news systems, aviation accidents gain relatively more attention.

Aviation accidents, compared with road traffic accidents, are more exceptional incidents and therewith more likely to make it into the news following the distortion bias. Against the backdrop of processes of mediatization, we, therefore, hypothesize that the relative attention for aviation accidents, compared with road accidents, goes up over time:.

H3: News attention for aviation accidents, relative to road accidents, rises over the years. A problematic distorted worldview among audiences might especially be created when media overrepresent aviation accidents.

The occurrence of such commercial airplane crashes is extremely rare, especially when compared with the risk associated with other modes of transportation. When so-called low-probability high-consequence accidents become more available in the minds of the audiences, this might complicate their rational decision making and risk assessment.

Extant research has pointed to discrepancies between public responses and the risk judgments of experts. Incidents, assessed as minor risk events by technical experts, can produce a massive societal response. People rather use social and psychological dimensions in their risk judgments, like its catastrophic potential of the risk or observable character Slovic, Fischoff, and Lichtenstein The same goes for aviation accidents.

Based on rational risk calculations as a function of the probability of occurrence assessment, indicators have shown a continuous improvement of aviation safety over the last decades, making air travel the safest transportation mode Li et al. Hence, the biased or ill-informed decision to refrain from commercial air travel—for example, in the wake of a fatal plane crash—is shaped by something else than statistical changes and real risk levels.

Within the field of risk research, scholars have considered news media as key actors in the social construction and definition of what acceptable levels of risk are Beck Here, mass media play an important role, both in the construction itself, as well as in criticizing and challenging institutional responses to those risks.

In light of the news biases addressed in this paper, news value-driven media coverage on isolated and catastrophic accidents might cause disproportional amplification of or attentiveness to risks, creating irrationally high levels of fear Berger Several related theoretical perspectives are useful in understanding how news content may contribute to a distorted worldview among audience members, shaping not only what we think about but also how we decide to act.

First, scholars who draw most directly on theories of communication science have provided a long history of how media content, especially negative news Soroka, Fournier, and Nir , affects what people think about, what is readily accessible in our minds i. Hence, audiences might learn about the frequency of occurrence of certain events based on what is presented on the news and consider that these numbers are applicable to the real world.

Second, psychological research highlights that individuals rely on available instances in their memory to make judgments—i. Accordingly, news about negative events like aviation accidents can increase perceived vulnerability to the degree that such stories are covered frequently.

For example, it is observed how news exposure biases perceived risk of terrorism to self and others Nellis and Savage , how negative coverage can create overly negative perceptions of minorities Gilliam and Iyengar , how news exposure explains salience of and fear for violent crimes rather than real crime rates Gross and Aday , and how media attention for aviation accidents can cause worries about airline safety Li et al.

Next, media-induced fear perceptions can also have behavioral effects. Exposure to crime news is, for example, found to be associated with avoidance behavior where people avoid certain areas because they overemphasize the possibility to become victimized there Smolej and Kivivuori In the context of our study, it is expected that when media disproportionally cover aviation incidents, audiences might engage in irrational avoidance behavior as they misperceive travel-related risk levels.

As plane crashes are vivid media exemplars, they might become more available in the minds of the audiences and therewith overshadow real risks like road traffic accidents. Whether the population irrationally switches their transportation choices from air travel to road travel, in light of media coverage on aviation accident, can become evident when such media coverage relates to increased road traffic relative to air traffic indicating that road travel is chosen as an alternative.

Such media-inspired avoidance behavior can be consequential Skogan ; Smolej and Kivivuori If people in large numbers decide to choose long-distance driving to refrain from commercial air travel, this likely increases the number of fatal road accidents as driving is statistically less safe than flying.

Therefore, this study explores if media attention to aviation accidents is related to an increase in fatal road accidents:. H4: The level of news attention for aviation accidents is significantly and positively related to road traffic relative to air traffic. H5: The level of news attention for aviation accidents is significantly and positively related to the number of fatal road accidents. This study relies on a longitudinal design to compare US news attention with real-world statistics.

The time period of — was selected as by this time commercial air travel has certainly become the safest transportation option and can be seen as an affordable alternative transportation mode to long-distance driving in the United States.

Real-world data were collected for the number of fatal road accidents and total road traffic as the main outcome variables for testing the impact of potentially biased coverage.

Fatal aviation accidents and total air traffic statistics are also collected as control variables in the analyses. All data were collected for the time period of January till December and are measured on a monthly aggregated level. The database of LexisNexis was consulted to obtain the number of news articles that cover transportation accidents in the period from until We relied on a combination of quality newspapers—i.

A census of all news articles about road traffic accident and accidents of commercial carriers was retrieved using a computer-assisted content analysis.

In a first step, search terms were developed to retrieve relevant articles from the LexisNexis archive. In a next step, we relied on an iterative process to improve the recall and precision of articles that actually contained references to accidents of motor vehicles or commercial carriers.

A comparison was made between the word range of 5, 10, 15, 20, 25, and 30 words. In the end, by systematically scanning the texts and the topics of the articles, we concluded that the range of ten words was the best approach to retrieving articles about motor vehicle traffic accidents and accidents of commercial carriers.

Table 1 presents an overview of number of articles about each type of accidents per newspaper. A monthly level measure of media attention was constructed by aggregating all the articles per month. For the analysis, this study relies both on the absolute and relative media attention for both types of incidents. The absolute measure reflects the total number of articles in the selected newspapers that discuss aviation or road accident.

In addition, a relative measure was constructed where the number of news articles about these accidents was divided by the total news circulation of newspapers in the United States. This measure allows for controlling whether over-time trends in news attention are not caused by fluctuations in newspaper circulation but rather show changes in relative attention. To obtain an indication of road traffic in the United States, we rely on traffic volume trends, measured in Millions of Miles, documented by the Federal Highway Administration.

These monthly statistics are based on hourly traffic count data reported by all US States. The monthly measure of fatal motor vehicle traffic crashes was the sum of fatal accidents that occurred in a given month and were reported by National Center for Statistics and Analysis. This measure is a census of fatal motor-vehicle traffic crashes in the fifty States, the District of Columbia, and Puerto Rico. To be included, an accident must involve a motor vehicle traveling on a roadway and result in the death of at least one person a vehicle occupant, driver, passenger, or a nonoccupant.

In addition, the total number of fatalities per fatal road accidents for each month is retrieved from United States Department of Transportation, National Highway Traffic Safety Administration. These statistics included number of passengers on domestic and international flights of major carriers, national carriers, large and medium regional carriers.

Together, these carriers account for most US commercial air traffic and can therefore be seen as a system-wide measure of commercial air traffic. This database provides an overview of the number of accidents and of commercial carriers and related number of fatalities both worldwide and in the United States.

To test the first and third hypotheses, we rely on ordinary least squares OLS regressions. H2, focusing on the autoregressive AR features of media attention for aviation accidents and how it is associated with real-world data, can be tested through estimation of partial adjustment Koyck autoregressive distributed lag ADL models. These regression models take the lag values of both dependent variable and independent variables into account to explain variation in media attention on a monthly level.

ARIMA modeling enables us to identify the size and delay of the effect of media coverage. In addition, these models take the series own past into account as it is assumed that the current values of time series—i. Several steps are taken to ensure that the models accurately considered the autocorrelation of the series. Before adding explanatory variables to the ARIMA models, the series need to be tested for stationarity, AR and moving average MA terms need to be determined, and the absence of autocorrelation of residuals need to be assessed Vliegenthart First, the Dickey—Fuller test was applied to test the assumptions regarding mean stationarity.

The terms help to build a model that reflects the past of the series and that includes all the previous information of the series over-time variance in the model. AR orders refer to the influence of pervious values and MAs are about the influence of residuals from previous values. Finally, the Portmanteau Q test for white noise indicates whether the residuals and the squared residuals are autocorrelated or not. We start with testing whether the actual occurrence of both aviation and road accidents show a different over-time trend as compared with news coverage of both accidents.

First, we test the effect of a linear monthly trend variable on the real-world statistics on number of aviation and road accidents.

These statistics suggest that the number of fatal aviation and road accidents decreases over the years. The figures in Supplementary Appendix visualize the over-time changes in total number of fatal road accidents Supplementary Figure A1 and aviation accidents Supplementary Figure A2.

Second, hypothesis 1 predicted that news attention for negative incidents—i. We test whether, despite the decreasing number of road and aviation accidents, the monthly number of articles about such accidents goes up over the years.

The number of articles per accidents is calculated by dividing the monthly articles relative to total news circulation about accidents by the total number of accidents that occurred in that given month. Figure 1 visualizes how the relative number of articles per aviation and road accident goes up over the years. In the Supplementary Appendix, Supplementary Figure A3 shows the over-time relative media attention for road and aviation accident and Supplementary Figure A4 shows the number of articles per accident.

In support of hypothesis 1, these findings indicate that over-time news attention per fatal road and aviation accident increases, whereas the frequency with which these accidents occur decrease over time. To test if news media follow their own logic when reporting on negative accidents, we compare media attention for aviation and road accidents with data on the actual occurrence of these accidents.

Accordingly, it was hypothesized that there would be a discrepancy between the frequency of occurrence of negative incidents—i. In these analyses we ask whether media coverage of aviation accidents is explained by actual statistics on fatal aviation accidents. In table 2 , two ADL models are shown, predicting the i absolute attention for aviation accidents and ii relative attention for aviation accidents. The statistically significant effects that can be observed for the AR terms of media attention indicates that attention for aviation accidents in the previous months explains attention in the next month.

In support of H2, table 2 shows the absence of an effect of the number of actual fatal aviation accidents, for any lags, on media attention, indicating that the occurrence of such accidents, in the same or previous months, is not leading for newspaper coverage on these accidents.

Note: Cells contain unstandardized regression coefficients with standard errors. The same AR tests were run for media coverage of road accidents. The ADL models aim to predict relative and absolute news attention for road accidents based on AR terms and actual statistics on fatal road accidents in the United States. A comparable pattern is observed as was found for aviation accidents.

Clear AR effects can be observed if we look at table 3 , whereas no effects of the actual number of fatal US road accidents on coverage is present. These findings together support H2 and suggest that news media follow their own mediatized logic and reality, rather than accurately representing what happens in the world.

Hypothesis 3 assumed that news attention for aviation accidents, relative to road accidents, rises over the years. Accordingly, the next regression analysis presents how the number of articles per aviation accident fatalities, relative to articles per fatal road accidents, varies over the years. The total number of articles per fatal road accidents was subtracted from the total number of articles per fatalities due to aviation accidents.

So, despite higher absolute media attention for road accidents, the relative attention for rare aviation accidents goes up over time, therewith H3 is confirmed. To determine the effects of media coverage of aviation accidents, we, in a first step, assess its effect on travel behavior H4.

By relying on monthly aggregated ARIMA modeling, we aim to see if road traffic, relative to air traffic, increases as a consequence of more news coverage on aviation accidents in previous months. A new variable was constructed to measure relative travel behavior by dividing total US road traffic with US aviation traffic and multiplying it by 10, This relative measure is used as it best reflects whether road traffic is chosen as an alternative for air travel since an increase in this measure indicates that the US population on average more often decided to travel by car rather than by commercial airlines.

The Dickey—Fuller tested indicated that the dependent times series—relative road travel—are stationary. To remove autocorrelation from the residuals, AR terms at lag 1, 3, 4, 6, 12, and MA terms at lag 1, 7, 12 were added. Supplementary Table A1 , in the Supplementary Appendix, presents the same three models but with the effect of relative news attention.

The first model is the model with only the AR and MA terms and the year and month as control variables. The final model also includes news attention for aviation accidents at T-1 and T-2 to test whether attention for aviation accidents in the previous two months results in less road traffic. The models show positive effects of media attention for T-1 on traffic behavior. According to the Pew survey, they are more distrusted than trusted by people who are mostly liberal and consistently liberal; and are more trusted than distrusted by people who are mixed, mostly conservative, and consistently conservative.

Note that this represents a further bias leaning than the "towards the left" sources. There are no direct parallels on the right. According to the Pew survey, they are more distrusted than trusted by people who are mostly liberal, consistently liberal; and are more trusted than distrusted by people who are mostly conservative, and consistently conservative.

It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results. University of Michigan Library Research Guides. Ask a Librarian. Search this Guide Search. What is "Fake News"? Why is this important? Where do news sources fall on the political bias spectrum?

How do you recognize bias in yourself and the media? The Liberal Media Does the media have a liberal bias? Here's one research-based answer to the question of liberal bias: The documentary The Myth of the Liberal Media: The Propaganda Model of News uses empirical evidence to look at ownership of the mainstream news media, filters that affect what news gets published, and examples of actual news coverage in order to show that conservative political and corporate interests significantly shape news coverage in the United States.

The myth of the liberal media : the propaganda model of news by Media Education Foundation Publication Date: Edward Herman and Noam Chomsky overturn one of the dominant myths in our political culture - the notion that mainstream media have a liberal bias.

Drawing on extensive empirical research, they reveal that in actuality the news media have become so subordinated to corporate interests that they are far to the right of the American people. Manufacturing Consent by Edward S.

U6 H New Sources on the Political Spectrum. What news sources are left-leaning, centrist, or right-leaning? Here are a couple of resources that can help:. Yet an unquestioning adherence to policies based on these principles might not always be the best thing.

Is democracy, for example, the best form of government for all people in all places at all times? Should government not be allowed to have any secrets? How far should government go to promote social equality? A modern term for it is the master narrative. Bush was a strong leader. Or he was dumb. These master narratives can become a kind of trap or rut. The journalist picks facts that illustrate a master narrative, or current stereotype, and ignores other facts.