University of Kwazulu-Natal

Fact Vs Framing How Media Bias Shapes Public Perception

Bonisiwe Shabane
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fact vs framing how media bias shapes public perception

In an era flooded with information, knowing the difference between what is true and what is twisted has never been more crucial. We often hear about “fake news:” blatantly false stories designed to deceive. However, media bias is more difficult to spot. While fake news is entirely false, media bias is often hidden: it misrepresents facts without making explicitly false statements. This subtlety makes it harder to detect as it erodes public trust and shapes opinions on skewed information. In this article, we will explore five common types of media bias and examine recent real-life examples.

We will also delve into how media bias impacts major societal events (such as the COVID-19 vaccine rollout) and investigate social media’s role in amplifying media bias. Finally, we will discuss how the public can identify media bias and find the most trustworthy and least biased sources. Media bias comes in many different forms, but let’s look at five common types: Negativity bias is a self-explanatory phenomenon built into psychology; bad news tends to stand out to us. News organizations, driven by the need for clicks and views, lean into this tendency. This bias prioritizes negative details and storylines to draw attention.

Media Bias refers to the way news stories are reported, often influenced by the political views of the journalists or the companies that own the news outlets. This bias can show up in different ways, such as the choice of words, the facts highlighted, or even the images used. Framing, on the other hand, is how an issue is presented to shape the audience's perception. For example, showing a wedding picture when talking about a law supporting same-sex marriage might evoke positive emotions, while focusing on concerns and debates can create a more negative response. Media bias is a significant issue because it affects how people think and feel about various topics, including politics and social issues. When people are unaware of bias in news reporting, it can lead to polarization in society.

Different news outlets might present the same story in contrasting ways, making it essential for readers to be aware of these differences to form well-rounded opinions. Recent advancements in technology, specifically in Natural Language Processing (NLP), offer tools to analyze and detect media bias. NLP helps in scanning large volumes of news content to identify biases and frames automatically. While traditional methods in Social Sciences often rely on detailed manual analysis, NLP can process information at scale, making it easier to spot trends in reporting. Both social sciences and NLP have their ways of addressing media bias and framing. Social science studies typically look at articles in detail, considering various aspects such as the sources of information and the broader context of the news report.

On the other hand, NLP usually focuses on analyzing specific articles or sentences but often misses the bigger picture, such as how issues evolve over time or differ across different outlets. The gaps between social sciences and NLP highlight the need for collaboration. By combining insights from both fields, researchers can create better models for understanding media bias. Social scientists can provide a theoretical backdrop that can inform NLP methodologies, while NLP can offer tools to process and analyze data more efficiently. Scientific Reports , Article number: (2025) Cite this article We are providing an unedited version of this manuscript to give early access to its findings.

Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply. Mainstream media, with its broad reach, plays a central role in shaping public opinion and thus warrants close scrutiny. Subtle forms of media bias–such as selective fact presentation and tone–can meaningfully influence public attitudes, even when reporting remains factually accurate. Although effects such as these have been widely studied by scholars of framing, much of the existing research focuses on specific topics and relies on manually constructed or pre-existing frames, limiting both scalability and... Here we introduce a novel framework that leverages large language models (LLMs) to generate synthetic news articles by systematically varying the selection and tone of the content while holding factual accuracy and other features...

We evaluate the impact of these alternative framings in a large, pre-registered randomized experiment (N = 2,141), and find that selective presentation of accurate information can significantly shift individuals’ policy views and emotional responses... These effects are consistently stronger for negative than positive framings and are more pronounced among individuals who say they are less informed about the topic. Our findings demonstrate the persuasive power of subtle bias in mainstream news as well as the value of LLMs as tools for scalable, controlled investigations of media effects. All survey data, experiment materials, and analysis code required for replicating the results can be found in the project’s OSF page (OSF link: https://osf.io/9g7sq/?view_only=189a8b9b2f644433bdbfcd4fc5c63ffe). Liedke, J. & Wang, L.

News platform fact sheet. Pew Res. Center 15, 253 (2023). Media bias is a critical factor influencing how the public perceives current events and political issues. In today’s fast-paced digital world, news consumers are inundated with information from a wide range of sources. However, not all media outlets present information in the same way, which can lead to varying levels of bias and reliability.

Understanding how media bias impacts public opinion is essential for fostering informed decision-making and promoting media literacy. Media bias refers to the perceived or real partiality of journalists and news producers in selecting and reporting stories. This can manifest in several ways, such as: Selection Bias: Favoring certain types of stories over others. Framing Bias: Presenting information in a way that influences interpretation. Partisan Bias: Supporting a specific political ideology or party.

Media bias and framing shape how we perceive news and politics. Journalists' choices in story selection, language, and presentation can sway public opinion on important issues. This affects how we understand complex topics and make decisions as voters. Recognizing bias helps us navigate the media landscape critically. By understanding framing techniques, we can better interpret news and form our own opinions. This knowledge empowers us to engage more thoughtfully in political discourse and democratic processes.

Framing effects are cognitive biases that influence the way people perceive and make decisions based on the way information is presented or framed. Essentially, the same information can produce different responses depending on how it is framed. This concept was first introduced by psychologists Amos Tversky and Daniel Kahneman in their seminal work on decision-making and behavioral economics. 1. Positive vs. Negative Framing: Information can be framed in a positive or negative manner.

For example, a medical treatment can be described as having a 90% success rate (positive frame) or a 10% failure rate (negative frame). People tend to respond more favorably to positive frames, even when the information is essentially the same. 2. Attribute Framing: This occurs when information is framed by emphasizing different attributes of the same thing. For instance, a car can be described as having great fuel efficiency or as being environmentally friendly, depending on what aspect the communicator wants to emphasize. People may respond differently based on the attribute highlighted.

3. Goal Framing: The way a goal or outcome is framed can impact decision-making. If a goal is framed as avoiding losses, people may be more risk-averse. Conversely, if the same goal is framed as achieving gains, people may be more willing to take risks. 4. Temporal Framing: The time frame in which an event or decision is presented can affect how people perceive it.

For example, if a task is framed as taking place in the distant future, people may procrastinate, but if it's framed as happening soon, they may act more urgently.

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